Gut microbiome correlates with plasma lipids in amyotrophic lateral sclerosis
© The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please e-mail: journals.permissionsoup.com..
Amyotrophic lateral sclerosis (ALS) is a complex, fatal neurodegenerative disease. Disease pathophysiology is incompletely understood but evidence suggests gut dysbiosis occurs in ALS, linked to impaired gastrointestinal integrity, immune system dysregulation and altered metabolism. Gut microbiome and plasma metabolome have been separately investigated in ALS, but little is known about gut microbe-plasma metabolite correlations, which could identify robust disease biomarkers and potentially shed mechanistic insight. Here, gut microbiome changes were longitudinally profiled in ALS and correlated to plasma metabolome. Gut microbial structure at the phylum level differed in ALS versus control participants, with differential abundance of several distinct genera. Unsupervised clustering of microbe and metabolite levels identified modules, which differed significantly in ALS versus control participants. Network analysis found several prominent amplicon sequence variants strongly linked to a group of metabolites, primarily lipids. Similarly, identifying the features that contributed most to case versus control separation pinpointed several bacteria correlated to metabolites, predominantly lipids. Mendelian randomization indicated possible causality from specific lipids related to fatty acid and acylcarnitine metabolism. Overall, the results suggest ALS cases and controls differ in their gut microbiome, which correlates with plasma metabolites, particularly lipids, through specific genera. These findings have the potential to identify robust disease biomarkers and shed mechanistic insight into ALS.
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2024 |
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Erschienen: |
2024 |
Enthalten in: |
Zur Gesamtaufnahme - volume:147 |
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Enthalten in: |
Brain : a journal of neurology - 147(2024), 2 vom: 01. Feb., Seite 665-679 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Guo, Kai [VerfasserIn] |
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Themen: |
16S rRNA sequencing |
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Anmerkungen: |
Date Completed 05.02.2024 Date Revised 06.03.2024 published: Print Citation Status MEDLINE |
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doi: |
10.1093/brain/awad306 |
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funding: |
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PPN (Katalog-ID): |
NLM362180121 |
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520 | |a © The Author(s) 2023. Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For permissions, please e-mail: journals.permissionsoup.com. | ||
520 | |a Amyotrophic lateral sclerosis (ALS) is a complex, fatal neurodegenerative disease. Disease pathophysiology is incompletely understood but evidence suggests gut dysbiosis occurs in ALS, linked to impaired gastrointestinal integrity, immune system dysregulation and altered metabolism. Gut microbiome and plasma metabolome have been separately investigated in ALS, but little is known about gut microbe-plasma metabolite correlations, which could identify robust disease biomarkers and potentially shed mechanistic insight. Here, gut microbiome changes were longitudinally profiled in ALS and correlated to plasma metabolome. Gut microbial structure at the phylum level differed in ALS versus control participants, with differential abundance of several distinct genera. Unsupervised clustering of microbe and metabolite levels identified modules, which differed significantly in ALS versus control participants. Network analysis found several prominent amplicon sequence variants strongly linked to a group of metabolites, primarily lipids. Similarly, identifying the features that contributed most to case versus control separation pinpointed several bacteria correlated to metabolites, predominantly lipids. Mendelian randomization indicated possible causality from specific lipids related to fatty acid and acylcarnitine metabolism. Overall, the results suggest ALS cases and controls differ in their gut microbiome, which correlates with plasma metabolites, particularly lipids, through specific genera. These findings have the potential to identify robust disease biomarkers and shed mechanistic insight into ALS | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a Research Support, Non-U.S. Gov't | |
650 | 4 | |a Research Support, N.I.H., Extramural | |
650 | 4 | |a 16S rRNA sequencing | |
650 | 4 | |a Mendelian randomization | |
650 | 4 | |a metabolomics | |
650 | 4 | |a motor neuron disease | |
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700 | 1 | |a Figueroa-Romero, Claudia |e verfasserin |4 aut | |
700 | 1 | |a Noureldein, Mohamed H |e verfasserin |4 aut | |
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700 | 1 | |a Savelieff, Masha G |e verfasserin |4 aut | |
700 | 1 | |a Hur, Junguk |e verfasserin |4 aut | |
700 | 1 | |a Goutman, Stephen A |e verfasserin |4 aut | |
700 | 1 | |a Feldman, Eva L |e verfasserin |4 aut | |
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