With your substantial risk of dementia you'll want your doctor to have EXACT PROTOCOLS for testing your gut microbiota and then changing it to the correct levels.
YOUR DOCTOR'S RESPONSIBILITY!
Gut–microbiota–microglia–brain interactions in Alzheimer’s disease: knowledge-based, multi-dimensional characterization
Alzheimer's Research & Therapy volume 13, Article number: 177 (2021)
Abstract
Background
Interactions between the gut microbiota, microglia, and aging may modulate Alzheimer’s disease (AD) pathogenesis but the precise nature of such interactions is not known.
Methods
We developed an integrated multi-dimensional, knowledge-driven, systems approach to identify interactions among microbial metabolites, microglia, and AD. Publicly available datasets were repurposed to create a multi-dimensional knowledge-driven pipeline consisting of an integrated network of microbial metabolite–gene–pathway–phenotype (MGPPN) consisting of 34,509 nodes (216 microbial metabolites, 22,982 genes, 1329 pathways, 9982 mouse phenotypes) and 1,032,942 edges.
Results
We evaluated the network-based ranking algorithm by showing that abnormal microglia function and physiology are significantly associated with AD pathology at both genetic and phenotypic levels: AD risk genes were ranked at the top 6.4% among 22,982 genes, P < 0.001. AD phenotypes were ranked at the top 11.5% among 9982 phenotypes, P < 0.001. A total of 8094 microglia–microbial metabolite–gene–pathway–phenotype–AD interactions were identified for top-ranked AD-associated microbial metabolites. Short-chain fatty acids (SCFAs) were ranked at the top among prioritized AD-associated microbial metabolites. Through data-driven analyses, we provided evidence that SCFAs are involved in microglia-mediated gut–microbiota–brain interactions in AD at both genetic, functional, and phenotypic levels.
Conclusion
Our analysis produces a novel framework to offer insights into the mechanistic links between gut microbial metabolites, microglia, and AD, with the overall goal to facilitate disease mechanism understanding, therapeutic target identification, and designing confirmatory experimental studies.
Introduction
Alzheimer’s disease (AD) is the leading cause of dementia and the most common neurodegenerative disorder, affecting over 5.5 million people in the USA and 47 million people worldwide [1]. AD is complex, with genetic, epigenetic, and environmental factors contributing to disease susceptibility and progression [2].
Trillions of bacteria in the human body (human microbiota) may affect human health and diseases by modulating host functions through small molecule metabolites. Undigested dietary components are fermented by microbiota to produce a wide array of metabolites such as bile acids, choline, and short-chain fatty acids (SCFAs) that are essential for human health [3,4,5]. Metabolite activities of gut microbiota provide a mechanistic connection between environmental factors and brain function and behavior [6,7,8]. The gut microbiota of AD patients has altered microbial diversity and is compositionally distinct from control age- and sex-matched individuals [9,10,11]. Recent studies showed that altered serum levels of bile acids, lipopolysaccharide, SCFAs, and trimethylamine-N-oxide (TMAO) were associated with cognitive impairment in AD [12,13,14,15].
In AD, microglia are involved in amyloid-β (Aβ) clearance in the brain and many innate immunity genes are associated with the risk of sporadic AD [16]. Microglia are the main neuroimmune cells involved in the development, normal functioning, aging, and injury of the central nervous system [16,17,18]. Gene variants in TREM2 and CD33 that modulate macrophage and microglial function increase the risk for late-onset AD [19]. There is increasing evidence that the interactions between the gut microbiota and brain innate immune system (gut–immune–brain axis) may modulate AD pathogenesis through microglial maturation and function [20,21,22]. Short-chain fatty acids (SCFAs), the end products of fermentation of dietary fibers by gut microbiota, play a major role in the maintenance of gut and immune homeostasis [23, 24]. SCFAs may play a key role in microbiota–gut–brain crosstalk. In vitro administration of SCFAs (microbial fermentation metabolites) regulated microglia homeostasis and obstructed Aβ protein aggregation [25]. Supplementation of SCFAs in germ-free mice rescued the immature genetic and morphological phenotype of microglia [20]. Despite such growing links, the mechanisms underlying how gut microbial metabolites including SCFAs interact with microglia and host genetics in promoting or protecting against AD remain largely unknown.
We have previously demonstrated that data-driven computational systems approaches have the potential in uncovering mechanistic links between microbial metabolites and human diseases [26,27,28,29]. For example, in a prior study, we provided evidence that trimethylamine N-oxide (TMAO), a human gut microbial metabolite of dietary meat and fat, was linked to AD [27], a finding that was subsequently confirmed by an experimental study [15]. In this study, we significantly expanded our prior work to produce the first comprehensive, multi-dimensional, systems framework of analyzing and identifying complex interrelationships among gut microbial metabolites, microglia, and AD at both genetic and functional levels. We first constructed a multi-model context-sensitive network to model complex and heterogeneous interrelationships among microbial metabolites, genes, pathways, and disease phenotypes. Then network-based prioritization algorithm prioritized microbial metabolites based on their relevance to microglia physiology and functions in AD. The overall goal of this study was to identify potential microglia–microbial metabolite–gene–pathway–phenotype interactions in AD with supporting evidence at genetic, functional, and phenotypic levels, which can set a foundation for others to conduct hypothesis-driven studies to test these interactions in experimental models or clinical samples.
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