Cargando…
Towards understanding brain-gut-microbiome connections in Alzheimer’s disease
BACKGROUND: Alzheimer’s disease (AD) is complex, with genetic, epigenetic, and environmental factors contributing to disease susceptibility and progression. While significant progress has been made in understanding genetic, molecular, behavioral, and neurological aspects of AD, relatively little is...
Autores principales: | , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2016
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5009560/ https://www.ncbi.nlm.nih.gov/pubmed/27585440 http://dx.doi.org/10.1186/s12918-016-0307-y |
_version_ | 1782451536212787200 |
---|---|
author | Xu, Rong Wang, QuanQiu |
author_facet | Xu, Rong Wang, QuanQiu |
author_sort | Xu, Rong |
collection | PubMed |
description | BACKGROUND: Alzheimer’s disease (AD) is complex, with genetic, epigenetic, and environmental factors contributing to disease susceptibility and progression. While significant progress has been made in understanding genetic, molecular, behavioral, and neurological aspects of AD, relatively little is known about which environmental factors are important in AD etiology and how they interact with genetic factors in the development of AD. Here, we propose a data-driven, hypotheses-free computational approach to characterize which and how human gut microbial metabolites, an important modifiable environmental factor, may contribute to various aspects of AD. MATERIALS AND METHODS: We integrated vast amounts of complex and heterogeneous biomedical data, including disease genetics, chemical genetics, human microbial metabolites, protein-protein interactions, and genetic pathways. We developed a novel network-based approach to model the genetic interactions between all human microbial metabolites and genetic diseases. We identified metabolites that share significant genetic commonality with AD in humans. We developed signal prioritization algorithms to identify the co-regulated genetic pathways underlying the identified AD-metabolite (brain-gut) connections. RESULTS: We validated our algorithms using known microbial metabolite-AD associations, namely AD-3,4-dihydroxybenzeneacetic acid, AD-mannitol, and AD-succinic acid. Our study provides supporting evidence that human gut microbial metabolites may be an important mechanistic link between environmental exposure and various aspects of AD. We identified metabolites that are significantly associated with various aspects in AD, including AD susceptibility, cognitive decline, biomarkers, age of onset, and the onset of AD. We identified common genetic pathways underlying AD biomarkers and its top one ranked metabolite trimethylamine N-oxide (TMAO), a gut microbial metabolite of dietary meat and fat. These coregulated pathways between TMAO-AD may provide insights into the mechanisms of how dietary meat and fat contribute to AD. CONCLUSIONS: Employing an integrated computational approach, we provide intriguing and supporting evidence for a role of microbial metabolites, an important modifiable environmental factor, in AD etiology. Our study provides the foundations for subsequent hypothesis-driven biological and clinical studies of brain-gut-environment interactions in AD. |
format | Online Article Text |
id | pubmed-5009560 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-50095602016-09-08 Towards understanding brain-gut-microbiome connections in Alzheimer’s disease Xu, Rong Wang, QuanQiu BMC Syst Biol Research BACKGROUND: Alzheimer’s disease (AD) is complex, with genetic, epigenetic, and environmental factors contributing to disease susceptibility and progression. While significant progress has been made in understanding genetic, molecular, behavioral, and neurological aspects of AD, relatively little is known about which environmental factors are important in AD etiology and how they interact with genetic factors in the development of AD. Here, we propose a data-driven, hypotheses-free computational approach to characterize which and how human gut microbial metabolites, an important modifiable environmental factor, may contribute to various aspects of AD. MATERIALS AND METHODS: We integrated vast amounts of complex and heterogeneous biomedical data, including disease genetics, chemical genetics, human microbial metabolites, protein-protein interactions, and genetic pathways. We developed a novel network-based approach to model the genetic interactions between all human microbial metabolites and genetic diseases. We identified metabolites that share significant genetic commonality with AD in humans. We developed signal prioritization algorithms to identify the co-regulated genetic pathways underlying the identified AD-metabolite (brain-gut) connections. RESULTS: We validated our algorithms using known microbial metabolite-AD associations, namely AD-3,4-dihydroxybenzeneacetic acid, AD-mannitol, and AD-succinic acid. Our study provides supporting evidence that human gut microbial metabolites may be an important mechanistic link between environmental exposure and various aspects of AD. We identified metabolites that are significantly associated with various aspects in AD, including AD susceptibility, cognitive decline, biomarkers, age of onset, and the onset of AD. We identified common genetic pathways underlying AD biomarkers and its top one ranked metabolite trimethylamine N-oxide (TMAO), a gut microbial metabolite of dietary meat and fat. These coregulated pathways between TMAO-AD may provide insights into the mechanisms of how dietary meat and fat contribute to AD. CONCLUSIONS: Employing an integrated computational approach, we provide intriguing and supporting evidence for a role of microbial metabolites, an important modifiable environmental factor, in AD etiology. Our study provides the foundations for subsequent hypothesis-driven biological and clinical studies of brain-gut-environment interactions in AD. BioMed Central 2016-08-26 /pmc/articles/PMC5009560/ /pubmed/27585440 http://dx.doi.org/10.1186/s12918-016-0307-y Text en © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Xu, Rong Wang, QuanQiu Towards understanding brain-gut-microbiome connections in Alzheimer’s disease |
title | Towards understanding brain-gut-microbiome connections in Alzheimer’s disease |
title_full | Towards understanding brain-gut-microbiome connections in Alzheimer’s disease |
title_fullStr | Towards understanding brain-gut-microbiome connections in Alzheimer’s disease |
title_full_unstemmed | Towards understanding brain-gut-microbiome connections in Alzheimer’s disease |
title_short | Towards understanding brain-gut-microbiome connections in Alzheimer’s disease |
title_sort | towards understanding brain-gut-microbiome connections in alzheimer’s disease |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5009560/ https://www.ncbi.nlm.nih.gov/pubmed/27585440 http://dx.doi.org/10.1186/s12918-016-0307-y |
work_keys_str_mv | AT xurong towardsunderstandingbraingutmicrobiomeconnectionsinalzheimersdisease AT wangquanqiu towardsunderstandingbraingutmicrobiomeconnectionsinalzheimersdisease |