An Integrative Analysis of Metagenomic and Metabolomic Profiling Reveals Gut Microbiome Dysbiosis and Metabolic Alterations in ALS: Potential Biomarkers and Therapeutic Insights

ALS is a severe neurodegenerative disorder characterized by motor neuron degeneration, gut dysbiosis, immune dysregulation, and metabolic disturbances. In this study, shotgun metagenomics and <sup>1</sup>H nuclear magnetic resonance (NMR)-based metabolomics were employed to investigate the altered gut microbiome and metabolite profiles in individuals with ALS, household controls (HCs), and nonhousehold controls (NHCs). The principal component analysis (PCA) explained 33% of the variance, and the partial least-squares discriminant analysis (PLS-DA) model demonstrate <i>R</i><sup>2</sup> and <i>Q</i><sup>2</sup> values of 0.97 and 0.84, respectively, indicating an adequate model fit. The relative bacterial abundance was 99.34% in the ALS group and 98.94% in the HC group. Among the ten identified genera, <i>Bifidobacterium</i>, <i>Lactobacillus</i>, and <i>Enterococcus</i> were more prevalent in ALS individuals, while <i>Lactiplantibacillus</i> and <i>Klebsiella</i> were more abundant in the HC group. We identified 70 metabolites, including short-chain fatty acids (SCFAs), branched-chain amino acids (BCAAs), carbohydrates, and aromatic compounds, using NMR. Orthogonal partial least-squares discriminant analysis (O-PLS-DA) explained 15.8% of the variance, with a clear separation between the ALS and HC groups. Univariate receiver operating characteristic (ROC) analysis identified three fecal metabolites with AUC values above 0.70, including butyrate (0.798), propionate (0.727), and citrate (0.719). These metabolites may serve as potential biomarkers for ALS. The statistical model for metabolic pathway analysis revealed interconnected pathways, highlighting the complexity of metabolic dysregulation, as well as potential microbial and metabolic biomarkers in ALS. These results highlight the role of gut microbiome alterations in ALS and suggest potential avenues for therapeutic intervention.

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Publication Details

Journal
ACS Chemical Neuroscience
Published
2025-06-09
DOI
https://doi.org/10.1021/acschemneuro.5c00254
Citations
6
Primary Topic
Gut microbiota and health
Type
article
Field-Weighted Citation Impact
4.84

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article

An Integrative Analysis of Metagenomic and Metabolomic Profiling Reveals Gut Microbiome Dysbiosis and Metabolic Alterations in ALS: Potential Biomarkers and Therapeutic Insights

Chandan Singh, Shashi Shekhar, Abhishek Pathak, Priyanka Gautam et al.
6 citations
ACS Chemical Neuroscience
Gut microbiota and health
4.84
article

An Integrative Analysis of Metagenomic and Metabolomic Profiling Reveals Gut Microbiome Dysbiosis and Metabolic Alterations in ALS: Potential Biomarkers and Therapeutic Insights

Chandan Singh, Shashi Shekhar, Abhishek Pathak, Priyanka Gautam, Rahul Yadav, Ranjeet Kumar Vishwakarma
article en
6 citations

Abstract

ALS is a severe neurodegenerative disorder characterized by motor neuron degeneration, gut dysbiosis, immune dysregulation, and metabolic disturbances. In this study, shotgun metagenomics and <sup>1</sup>H nuclear magnetic resonance (NMR)-based metabolomics were employed to investigate the altered gut microbiome and metabolite profiles in individuals with ALS, household controls (HCs), and nonhousehold controls (NHCs). The principal component analysis (PCA) explained 33% of the variance, and the partial least-squares discriminant analysis (PLS-DA) model demonstrate <i>R</i><sup>2</sup> and <i>Q</i><sup>2</sup> values of 0.97 and 0.84, respectively, indicating an adequate model fit. The relative bacterial abundance was 99.34% in the ALS group and 98.94% in the HC group. Among the ten identified genera, <i>Bifidobacterium</i>, <i>Lactobacillus</i>, and <i>Enterococcus</i> were more prevalent in ALS individuals, while <i>Lactiplantibacillus</i> and <i>Klebsiella</i> were more abundant in the HC group. We identified 70 metabolites, including short-chain fatty acids (SCFAs), branched-chain amino acids (BCAAs), carbohydrates, and aromatic compounds, using NMR. Orthogonal partial least-squares discriminant analysis (O-PLS-DA) explained 15.8% of the variance, with a clear separation between the ALS and HC groups. Univariate receiver operating characteristic (ROC) analysis identified three fecal metabolites with AUC values above 0.70, including butyrate (0.798), propionate (0.727), and citrate (0.719). These metabolites may serve as potential biomarkers for ALS. The statistical model for metabolic pathway analysis revealed interconnected pathways, highlighting the complexity of metabolic dysregulation, as well as potential microbial and metabolic biomarkers in ALS. These results highlight the role of gut microbiome alterations in ALS and suggest potential avenues for therapeutic intervention.

ACS Chemical NeuroscienceVol. 16(14)
Shanghai Institute for Science of Science (CN), Institute of Medical Sciences (IN), Banaras Hindu University (IN)
Indian Council of Medical Research
Zero hunger
Openalex Percentile: Top 5%
Gut microbiota and health
4.84
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