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| Funder | AGENCY FOR TOXIC SUBSTANCES AND DISEASE REGISTRY |
|---|---|
| Recipient Organization | University of Michigan At Ann Arbor |
| Country | United States |
| Start Date | Sep 30, 2022 |
| End Date | Sep 30, 2025 |
| Duration | 1,096 days |
| Number of Grantees | 1 |
| Roles | Principal Investigator |
| Data Source | NIH (US) |
| Grant ID | 10704221 |
ABSTRACT Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by progressive motor neuron loss. Few treatment options with limited efficacy are available; therefore, new therapies are critically needed. However, the underlying mechanisms of disease pathogenesis must be better understood to identify
disease biomarkers and therapeutic targets. Numerous biological systems and pathways are implicated in ALS including the gut microbiome, the metabolome, and the immune system. Our own studies show that these peripheral systems not only change over time but are associated with disease progression. In particular, the
gut microbiome is linked to clinical, metabolomic, and immune metrics, suggesting that there is an integrated disease pathway network contributing to ALS. In the proposed research, we will examine the underlying mechanisms by which these peripheral pathways impact ALS progression to enhance the design of future trials
and therapies. More specifically, we will examine the potential mechanisms by which changes in the gut microbiome alter peripheral metabolites and immune cells in ALS. The overall objective of this Option B study is to use the existing infrastructure and data pipelines from two ongoing R01-funded ALS studies to identify
cross-sectional and longitudinal associations between the ALS microbiome and clinical, metabolomic, and immune metrics of disease. We hypothesize that the microbial composition of ALS subjects – either individual bacterial communities or clusters of bacterial populations – will be associated with ALS progression as
measured by the ALS functional rating scale-revised (ALSFRS-R) (Aim 1). In addition, we hypothesize that specific bacterial populations or population clusters will be associated with changes in both metabolic profiles (Aim 2) as well as immune metrics (Aim 3) and that metabolic and immune changes will be associated with
altered disease progression. Completion of the study will identify integrated microbial, metabolic, and immune pathways that can be used as biomarkers or therapeutic targets for future clinical trials.
University of Michigan At Ann Arbor
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