Skip to main content

Microbial-derived metabolites as a risk factor of age-related cognitive decline and dementia

Abstract

A consequence of our progressively ageing global population is the increasing prevalence of worldwide age-related cognitive decline and dementia. In the absence of effective therapeutic interventions, identifying risk factors associated with cognitive decline becomes increasingly vital. Novel perspectives suggest that a dynamic bidirectional communication system between the gut, its microbiome, and the central nervous system, commonly referred to as the microbiota-gut-brain axis, may be a contributing factor for cognitive health and disease. However, the exact mechanisms remain undefined. Microbial-derived metabolites produced in the gut can cross the intestinal epithelial barrier, enter systemic circulation and trigger physiological responses both directly and indirectly affecting the central nervous system and its functions. Dysregulation of this system (i.e., dysbiosis) can modulate cytotoxic metabolite production, promote neuroinflammation and negatively impact cognition. In this review, we explore critical connections between microbial-derived metabolites (secondary bile acids, trimethylamine-N-oxide (TMAO), tryptophan derivatives and others) and their influence upon cognitive function and neurodegenerative disorders, with a particular interest in their less-explored role as risk factors of cognitive decline.

Background

Age is the predominant risk factor for cognitive decline. Whilst some decline in cognition is considered an inevitable part of healthy ageing, deleterious changes in cognition, including mild cognitive impairment (MCI) and age-related dementias (e.g., Alzheimer’s disease, AD), are estimated to impact approximately 15% and 11% of the population over 65 years respectively [1, 2]. By 2050, the global elderly population is expected to increase by 21% [2], increasing incidences of cognitive decline [3]. Cognitive decline exacerbates broad social and economic issues, including depression, social withdrawal, difficulties performing everyday tasks, drastic reductions in quality of life and greater reliance on others (social care) [4]. Understanding how to promote healthy ageing whilst resisting aberrant changes in cognition is therefore becoming a priority.

Addressing modifiable risk factors can delay the onset, or even ameliorate cognitive decline [5], whilst assisting with the identification of asymptomatic individuals with an increased chance of developing the condition in the future [6]. Currently, hypertension [7], diabetes mellitus [8, 9], arteriosclerosis [10], obesity [11] and hypercholesterolemia [12] are the most significant risk factors associated with age-related cognitive decline among others [13]. Given the connection between cognition and these metabolic diseases, it is perhaps unsurprising that dietary factors can elicit a substantial influence upon cognitive function [14] through the modulation of a microbiota-gut-brain axis [15]. The microbiota-gut-brain axis is a complex communication system bridging the gut, liver and the central nervous system (CNS) that is modulated by the microbiome, a collection of 1014 microorganisms with an extensive functional gene repertoire [16]. These microorganisms predominantly reside in the gut, metabolising dietary compounds into a vast range of metabolites. Metabolites can cross the intestinal epithelial barrier; a structure connected by tight junction proteins, lamina propria and reinforced by mucosal secretions [17], primarily via active transport, and enter systemic circulation. From here, metabolites can directly initiate physiological responses by crossing the blood–brain barrier (BBB) and influencing the CNS [18], or indirectly via vagus nerve stimulation (Fig. 1) [19].

Fig. 1
figure 1

Microbial metabolites can directly and indirectly modulate the CNS through immune, neuronal and direct metabolite mediated pathways within the microbiota-gut-brain axis. In the gut lumen, dietary products can be metabolised by microbiota into neuroactive compounds, including neurotransmitters, (e.g., serotonin, dopamine), amino acids (e.g., tryptophan, tryptamine) and other microbial-derived metabolites (e.g., short-chain fatty acids, trimethylamine (TMA)). These compounds subsequently communicate with the central nervous system either directly, travelling through the portal vein, liver and crossing the blood–brain barrier, or indirectly via the production of neurotransmitters by enterochromaffin cells (ECC) or immune pathways (stimulated immune cells produce cytokines that can enter the blood or stimulate the vagus nerve)

The capability of microbial-derived bioactive metabolites to influence the CNS provides a novel mechanistic pathway for cognitive decline, warranting its further exploration. Within the gastrointestinal (GI) tract, microbiota populations are in part reflective of their local physiological conditions. The small intestine, due to its proximity with the stomach, contains high concentrations of acids, oxygen and antimicrobials, thereby restricting bacterial growth to predominantly fast-growing anaerobes that can adhere to epithelia or mucus [20]. Conversely, colonic regions promote much denser bacterial communities, dominated by anaerobes such as Prevotellaceae and Lachnospiraceae, that can digest complex carbohydrates [21]. Numerous intrinsic factors (e.g., genetics, immune response, metabolites) and extrinsic factors (e.g., diet, lifestyle) also impact gut microbial composition, making it an attractive therapeutic intervention target [22]. The composition of these microbial communities determines the concentration of neurotransmitters or neuromodulators (including microbial-derived metabolites) released into circulation. Broad deviations in these microbial compositions, often referred to as “dysbiosis”, condition distinctly different metabolic profiles that may contribute to cognitive decline [23, 24]. Gut microbial composition is known to be significantly altered in patients with MCI, a transitional stage preceding AD, suggesting microbial changes may occur in the early stages of cognitive decline and influence its progression [25,26,27,28,29].

Intestinal microbiota possess the capacity to produce hundreds of metabolites [30, 31], yet the influence of these compounds on cognitive health have not been uncovered. The present review details the roles of newly emerging microbial-derived metabolites that are less-explored in the current literature in the context of cognitive health and provide an additional in-depth discussion of their use as potential indicative factors of cognitive decline.

Age-related cognitive declines

As we age, some of our cognitive abilities decline. Cognitive capabilities such as verbal skills, remain largely unaffected by brain ageing and can even improve over time [32]. Other essential capabilities, including mental reasoning, memory (in particular episodic, working and recognition memory) and processing speed, steadily deteriorate with age (See review [33] for further information). During ageing, the brain undergoes various structural and functional changes. The most apparent being a gradual shrinkage of the brain, alongside an increase in ventricular space and cerebrospinal fluid (CSF) [34, 35]. Brain atrophy increases in the elderly in an anterior–posterior gradient, with the most severe consequences taking place in the prefrontal regions [36, 37]. A reduction in white matter (the nerve fibres connecting different brain regions) integrity has been linked with normal cognitive ageing, impairing the transfer of information between cortical regions [38], an essential process for higher cognitive functioning [39].

Structural neuroimaging highlights differing trends in the neurobiology of pathological ageing and detrimental cognitive decline. Here, individuals are more likely to experience reductions in gray matter in the dorsolateral and medial prefrontal, parietal, and lateral temporal regions [40, 41], alongside a loss of white matter integrity in the cingulum, corpus callosum, and superior longitudinal fasciculus [42,43,44]. This is instead of a decline in the frontal regions that typically occurs in healthy ageing.

AD is also associated with volume loss in the medial temporal lobe, a brain region highly associated with memory functions. Reduction typically starts in the anterolateral entorhinal cortex and advances medially across the remaining entorhinal cortex to the hippocampus [45, 46], with atrophy occurring at rates of 4.9–8.2%. In healthy ageing, atrophy in these regions occurs at a lower rate, diverging from pathological ageing, at 0.2–3.8% [46]. More recently, using longitudinal MRI and PET data, a similar divergence in volume loss has been noted in the locus coeruleus [47].

Finally, the default mode network (DMN), a resting-state network associated with cognitive processes of oneself (e.g., autobiographical memory), demonstrates connectivity patterns that distinguish healthy ageing from AD. Results from a task free-fMRI suggest AD patients have an accelerated ageing pattern of connectivity [48] and decreased resting-state activity in the posterior cingulate and hippocampus when compared with age-matched controls [49]. However, the biological mechanisms behind the heterogeneity of age-related cognitive decline are complex and not well understood.

The microbiota-gut-brain axis in the context of ageing and cognitive decline

The human gut microbiome represents a complex community of microbes that live in a mutualistic relationship with their host. Initially, these microorganisms were considered to be solely responsible for intestinal processes (fermentation of carbohydrates, synthesis of vitamins and xenobiotic metabolism) [50]. However, over the last 15 years, this notion has been revised, owing to increasing evidence of a bidirectional communication system between the CNS and the GI tract, more commonly referred to as the ‘gut-brain axis’.

The gut-brain axis encompasses the CNS, the autonomic and enteric nervous system, and peripheral nerves and is vital for maintaining homeostasis. Signals from the brain control the secretory and sensory function of the gut, whilst the brain and gut communicate via physiological channels including the neuroendocrine, autonomic nervous system, neuroimmune pathways and molecules synthesised from gut microbes [51]. Since the gut microbiota is integral to the modulation of this communication at different levels (from the gut lumen to the CNS) and chronologically as we age, many have broadened the term to ‘microbiota-gut-brain axis’ [52]. Indeed, the existence of the microbiota-gut-brain axis is supported by substantial preclinical and human evidence, highlighting its effect on different cognitive domains. Firstly, germ-free (GF) mice show that the brain is markedly affected by the absence of microbiota, exhibiting deficiencies in learning, memory recognition and emotional behaviours [53,54,55,56]. These behavioural changes were accompanied by altered brain-derived neurotrophic factor (BDNF) expression in the hippocampus [54, 57, 58], a molecule inherently linked with synaptic plasticity and cognitive function [59,60,61], and significant microbiota-associated changes in the quantity of dopamine and activation of serotonin synthesis pathways [62,63,64,65], suggesting an important role of microbiota in memory, brain health and behaviour. Secondly, chronic antibiotic depletion of microbiota populations alters tryptophan metabolism and the expression of key cognitive signalling molecules in the brain such as BDNF, N-methyl-d-aspartate receptor subunit 2B (NR2B), serotonin transporter, neuropeptide Y system, oxytocin and vasopressin [66, 67]. These changes are associated with long-lasting effects on cognition and increases in anxiety-related behaviours [66, 68]. Finally, administering specific prebiotics/probiotics modulates behaviour in both rodents and humans, including changes in depression, anxiety and stress [57, 69,70,71,72,73], alongside changes in immune markers, hippocampal synaptic efficacy and tryptophan metabolism [74, 75].

As we age, microbiota composition and function changes [76]. In humans, this has been associated with a decrease in species diversity, a reduction in Clostridiales and Bifidobacterium and a rise in Proteobacteria and pathobionts such as Enterobacteriaceae [76, 77]. However, abnormal alterations in intestinal microbiota composition, as seen in early cognitive decline and AD [25, 78], are associated with local and systemic inflammation, and dysregulation of the microbiota-gut-brain axis [79]. Advances in sequencing technologies have enabled us to investigate the association between cognitive decline and gut dysbiosis at the phylum level. These studies have highlighted differences in taxonomic levels of Bacteroides, Firmicutes, Actinobacteria, Ruminococcus, Lachnospiraceae, and Selenomonadales between AD patients in comparison to controls [25, 78, 80,81,82].Such dysregulation has been associated with an increase in inflammatory markers, cytokines and the permeability of the gut epithelial barrier (‘leaky gut’), resulting in excessive leakage of bioactivate molecules, such as short-chain fatty acids (SCFAs), kynurenines, melatonin, histamine, bile acids, and neurotransmitters, into the blood. The resulting increase in neuroactive products can no longer efficiently be removed by the body’s next barrier; the liver, and therefore can cause a variety of physiological changes directly and indirectly affecting the CNS, including further decrease in BBB function. In the elderly population, this dysregulation becomes particularly relevant, as the BBB becomes more permeable with age [83]. A more permeable BBB allows an increased influx of harmful blood components, including microbial metabolites, into the brain; a feature seen in AD patients (reviewed by [84]). This process promotes neuroinflammation and macrophage dysfunction, leading to neural injury and ultimately a reduction in cognitive function [85, 86].

As previously outlined, the gut can also influence the brain indirectly through the vagus nerve activation. The vagus nerve consists of 80% afferent and 20% efferent fibres [87]. Afferent fibres connect to all four layers of the digestive tract, but do not cross the epithelial layer and therefore are not in direct contact with gut microbiota. As a result, the microbiota activates these fibres indirectly via the release of metabolites or bacterial products. Enteroendocrine cells (ECCs) make up approximately 1% of intestinal epithelial cells and can detect signals from the microbiota through toll-like receptors (TLR), capable of identifying bacterial compound such as lipopolysaccharides (LPS) [88], or through receptors activated by microbiota-derived metabolites such as SCFAs [89]. ECCs can subsequently interact with vagal afferent fibres through the release of serotonin or gut hormones [90, 91]. This indirect signalling between the gut microbiota and the brain via the vagus nerve can modulate certain cognitive functions. For example, rodents fed with the probiotic L. rhamnosus for 28 days had a decrease in anxiety-related behaviour, whilst inducing region-dependent alterations in γ-aminobutyric acid (GABA) receptor [92]. Importantly, this result only occurred with an intact vagus nerve, as mice undergoing a vagotomy did not display these behavioural and neurochemical changes. Similarly, in a colitis model, the normalisation of anxiety-like behaviours by the probiotic Bifidobacterium longum NCC3001 was found to be vagally dependent [93]. However, the total effects of the microbiome are not solely dependent on the vagus nerve stimulation, as mice orally receiving a mixed antimicrobial treatment had altered exploratory behaviour and hippocampal BDNF, independently of vagal integrity [94]. Together, these data emphasise that while the vagus nerve provides a crucial bridge allowing communication between the gut, its microbiome and brain, there are also other essential routes of communication comprising the microbiota-gut-brain axis, indicating its complex connectivity.

The microbiota-gut-liver-brain axis

The relationship between the gut, liver and brain has increasingly been highlighted in recent years due to a high prevalence of liver disease, which is commonly accompanied by clear and global cognitive impairment (hepatic encephalopathy) [95, 96]. The gut and liver are linked by the portal vein, biliary tract and systemic circulation, allowing microbial and host-derived metabolites to influence liver function. Conversely, the liver acts as a vital barrier, removing potentially harmful compounds from the blood using a range of hepatic immune cells, including Kupffer cells, hepatic stellate cells and natural killer cells [97], modulating the concentration of metabolites directly and indirectly influencing the CNS. The liver also controls unrestricted bacterial growth in the gut, maintaining gut eubiosis, through the transport of bile salts through the biliary tract into the intestinal lumen leading to the secretion of antimicrobial compounds [98, 99]. For example, bile acids can bind to the FXR receptor in enterocytes, initiating the production of antimicrobial peptides such as angiogenin 1 and RNAse family member 4, which can inhibit bacterial overgrowth in the gut and intestinal barrier dysfunction [100]. Gut dysbiosis causes an imbalance of microbial and host-derived products, reducing the epithelial barrier function and causing increased leakage in the system. Long-term, this process can initiate metabolic disorders in the liver, promoting liver damage (reviewed by [101]). As such, liver damage has been found to correlate with the severity of gut dysbiosis [102]. Since a diseased liver cannot effectively remove harmful products from the blood or inhibit the overgrowth of bacteria [103,104,105], this process can accelerate microbiota-gut-brain axis dysregulation and ultimately cognitive decline. Thus, when considering the occurrence of cognitive decline associated with microbial-derived metabolites, the role and function of the liver cannot be ignored.

Microbial-derived metabolites and cognitive decline

Bile acids

Humans produce large, hydrophilic pools of primary bile acids (BA) from cholesterol in the liver that are secreted into bile (Fig. 2). BAs are largely synthesised via two biosynthetic pathways: the classical pathway and the alternative pathway [106]. The classic pathway produces the majority of BAs in humans (~ 90%) and is initiated by the cholesterol 7α-hydroxylase (CYP7A1) enzyme to synthesise the primary BAs cholic acid (CA) and chenodeoxycholic acid (CDCA) [107]. The alternative pathway contributes less than 10% of BA synthesis (with more minor pathways contributing the remainder) and is initiated by sterol 27-hydroxylase (CYP27A1) [108]. After synthesis in the liver, CA and CDCA can be conjugated with hydrophilic taurine or glycine residues before they are secreted from hepatocytes into the bile canaliculi. They are stored in the gallbladder ready to be distributed into the small intestine following a meal to expedite digestion and emulsify dietary lipids and fat-soluble vitamins. Once secreted into the small intestine, more hydrophobic secondary BAs are formed by gut bacteria and are subsequently excreted or reabsorbed in the ileum to enter the enterohepatic circulation and recycle back to the liver [109]. This efficient process ensures BAs are recycled between 4 to 12 times a day [106].

Fig. 2
figure 2

Bile acids, TMAO and tryptophan metabolic pathways and their links to the brain. Primary bile acids are produced from cholesterol breakdown in the liver. They can be conjugated with taurine or glycine residues before travelling to the gut, where they are deconjugated and converted to secondary bile acids via microbial action. Bile acids have been found in the brain of humans and rodents suggesting they can cross the blood–brain barrier via either diffusion (unconjugated) or active transport (conjugated) and influence the central nervous system. TMAO is produced via a two-stage process. TMA is first formed from the microbial conversion of choline in the gut. TMA then travels to the liver, where the FMO1/3 enzyme converts it to TMAO. Recent evidence found TMAO in human brains, indicating it can cross the blood–brain barrier. Tryptophan can be metabolised via three key pathways. Firstly, via gut microbial action, tryptophan can be converted via the indole pathway into numerous indole derivatives, or into the amino acid, tryptamine. Indoles and tryptamine are known to cross the BBB. Secondly, around 3% of dietary tryptophan is metabolised into serotonin and melatonin via numerous enzymes in the serotonin pathway. Notably, serotonin produced in the gut cannot cross the blood–brain barrier. However, the serotonin precursor, 5-hydroxytryptophan, and serotonin derivatives, N-acetylserotonin and melatonin, can cross the blood–brain barrier and influence the central nervous system. Finally, the majority of tryptophan (~ 90–95%) is metabolised via the kynurenine pathway, of which 90% occurs in the liver. This pathway is initiated by the TDO enzyme in the liver and the IDO enzyme in the brain. Only kynurenine, 3-hydroxykynurenine and tryptophan itself can cross the blood–brain barrier. However, once in the brain, tryptophan can be metabolised via both the kynurenine and serotonin pathways to form the pathway’s intermediates

In the brain, cholesterol can be metabolised by a final pathway known as the neural cholesterol pathway. As the brain is one of the more sensitive organs to hypercholesterolemia, this cholesterol breakdown is essential to maintaining brain health [110]. Excess cholesterol becomes oxidised into 24- and 25-hydroxycholesterol by cholesterol 24-hydroxylase (CYP46A1), an enzyme primarily expressed in the brain [111]. Once 24(S)-hydroxycholesterol is formed, it can pass through the BBB and enter circulation. From here, 24(S)-hydroxycholesterol travels back to the liver to be metabolised by CYP39A1 and continue in BA synthesis [111]. In mice with mutated CYP46A1 function, 24(S)-hydroxycholesterol is not formed and is associated with impairments in spatial, associative and motor learning, highlighting the importance of this pathway for maintaining cognitive function [112].

BAs in the brain

Over 20 conjugated and unconjugated BAs and their receptors have been reported in both human and rodent brains [110, 113,114,115], suggesting BAs can not only cross the BBB but also bind to nuclear receptors and initiate physiological responses [115, 116]. However, the mechanism by which BAs cross the BBB is still uncertain. Unconjugated BAs may diffuse across the BBB as CA, CDCA and deoxycholic acid (DCA) are known to diffuse across phospholipid bilayers [117] and concentrations in the brain correlate with serum levels [113]. On the other hand, conjugated bile salts must cross the BBB via active transport due to their hydrophilic anionic structure at physiological pH [118, 119]. Indeed, members of the solute carrier (SLC) family, such as the organic anion transporting polypeptides (OATP1A4 and 1C1) [120] and the apical sodium-dependent bile acid transporter (ASBT or SLC10A2) [121], and members of the ATP-binding cassette transporters (ABC) family such as ABCC2 and ABCC4 [122, 123] have been identified in the brain. Conversely, Baloni and colleagues through a large-scale transcriptomics analysis of 2,114 post-mortem brains identified only three BA transporters (ABCC1, ABCC4 and SLC51A/SLC51B) in the brain [110]. The primary role of these transporters is to reduce the concentration of cytotoxic molecules by transporting them into the bloodstream [124]. Yet, since these transporters occur on both the basolateral (blood-facing) and apical (brain-facing) side [125], they may also transport molecules into the CNS from systemic circulation, indicating a potential endogenous signalling role of BAs in the brain. However, there is still a lack of direct evidence of in vivo transport of BA over the BBB [125].

BAs and cognitive function

While BA function in the GI tract is well-characterised, significantly fewer studies investigate their effect in the brain, limiting our knowledge [111]. Accumulating evidence suggests that cognition can be influenced by the dysregulation of BA synthesis and metabolism. Indeed, BAs profiles are reportedly altered in cases of MCI and AD, with an increase in cytotoxic secondary BAs and a decrease in primary BAs, suggesting a role of the gut microbiome in the disease progression [126]. Specifically, increased serum concentrations of the secondary BA DCA have been observed in AD patients. DCA has been previously linked with the presence of cognitive symptoms [127] and can modulate mitochondrial pathways causing apoptosis in a variety of tissues and cell types [128]. BA dysbiosis, resulting from either liver or microbiota dysfunction, has been subsequently linked to changes in gut permeability, possibly through FXR and TGR5 receptor signalling, and inflammation, promoting further bacterial dysbiosis in the gut [129]. Inflammation is also a known trigger of microglial activation and reduced neuroplasticity [130], possibly through the production of reactive oxygen species [131], highly reactive chemical molecules that have been previously linked with cognitive decline and AD [132, 133]. Although, some have proposed an important physiological role of ROS in brain metabolic signalling [134].

Alternatively, some BAs have been reported to have neuroprotective effects in the brain (for summary see Table 1). The primary BA CA has been identified as an LXR ligand, which in turn promoted midbrain neural development and neurogenesis in zebrafish [135]. Tauroursodeoxycholic acid (TUDCA), a secondary conjugated BA, can suppress amyloid- β (Aβ) -induced apoptosis in neuronal cell cultures and rodent neurons through the inhibition of the E2F-1/p53/BAX pathway [136, 137]. Similarly, in APP/PS1 double-transgenic mice, providing a TUDCA enriched diet for 6 months reduced Aβ aggregates, neuronal apoptosis, memory deficits and phosphorylation of TAU [138,139,140]. TUDCA has also been shown to induce anti-inflammatory effects in a mouse model of acute neuroinflammation through its binding and activation of G protein‐coupled bile acid receptor 1/Takeda G protein‐coupled receptor 5 (GPBAR1/TGR5), a receptor expressed on microglia [141]. Finally, in adult rats, TUDCA also enhanced neural stem cell proliferation and early neurogenesis [142], processes that are significantly diminished in AD (reviewed by [143]), with some research suggesting increasing neurogenesis may counteract AD pathological outcomes. Together these findings provide convincing evidence that cognition can be influenced by BAs. Yet further research is required to determine the involvement of specific BA transporters and receptors, as well as the subsequent mechanisms in their neuroprotective and detrimental effects.

Table 1 Bile acids and their impact on cognition and dementia

BA as a risk factor of cognitive decline

The association between BAs and cognitive decline, in particular with known AD pathologies [152], has raised speculations that BA profiles could be used as a risk factor of cognitive decline. Currently, there is limited research into the topic. However, Olazarάn and colleagues investigated a large cohort of patients with MCI and AD and identified DCA as being independently associated with the presence of cognitive symptoms [127]. Mapstone et al. identified seven blood-based markers which included glycoursodeoxycholic acid (GUDCA) and could predict the onset of AD or amnestic MCI with 2–3 years with an accuracy of over 90% [153]. Similarly, Marksteiner and colleagues were able to differentiate between healthy controls and AD patients from the concentration of lithocholic acid (LCA) in plasma [154]. However, it should be noted this study utilised a relatively small sample size (n = 80) and did not control for the effects of varied diets between individuals, warranting further investigation into the use of BAs as risk factors of cognitive decline.

TMAO

Trimethylamine N-oxide (TMAO) is a microbial-dependent metabolite generated by the breakdown of dietary fish, meat and fat [147, 155]. Trimethylamine (TMA), the precursor to TMAO, is produced from the metabolism of choline, L-carnitine and phosphatidylcholine by anaerobic microbes in the gut, predominantly located in the small intestine (Fig. 2) [144, 145]. TMA subsequently travels through the portal vein to the liver where it is oxidised by flavin-containing monooxygenase 1 and 3 (FMO1 and FMO3) to form TMAO [146]. Once formed, TMAO can enter the systemic circulation, hence TMAO plasma levels (typically 3 μmol/L in healthy individuals [148]) have been found to correlate with the gut microbial composition [149].

TMAO and the brain

In vivo studies have identified TMAO in the CSF of both mice and humans, implying that circulating TMAO can influence the CNS [147, 150]. The high concentrations of TMAO detected in the human CSF suggests liver-derived TMAO can cross the BBB, however, the penetration mechanism is unclear [151]. It is also possible a portion of TMAO found in the brain may be synthesised de novo, as FMO3, the enzyme required to convert TMA to TMAO, has been detected in the adult brain [156].

TMAO and cognitive decline

Over the last decade, TMAO has received increased attention in medical studies due to its links with cardiovascular diseases [157], obesity, diabetes [158], chronic kidney disease [159], metabolic syndrome [160], brain ageing and cognitive impairment [161] and neurodegenerative disorders such as AD [147]. However, the influence of TMAO on cognition is unclear. In fact, there is much controversy as to whether TMAO promotes a positive or detrimental effect on the brain.

Both experimental [161,162,163] and clinical [164,165,166] studies suggest high levels of TMAO may be causally linked to cognitive decline. Vogt and colleagues discovered an increase in CSF TMAO in AD patients in comparison to controls, suggesting the metabolite may contribute to decreasing neurological function [147]. However, a recent Mendelian randomisation study disputes this relationship [167].

The mechanisms by which TMAO may contribute to cognitive decline remain broad and unclear. TMAO reportedly modulates lipid and hormonal homeostasis [147], encourages platelet hyperreactivity via the enhancement of stimulus-dependent release of calcium ions [168], modifies cholesterol and sterol breakdown, reduces reverse cholesterol transport [169], and increases endothelial dysfunction through the induction of the NLRP3 inflammasome [170]. Rodents fed supraphysiological doses of TMAO also suggest the metabolite promotes neuronal senescence, oxidative stress, mitochondrial dysfunction and prevents mTOR signalling [161]. Furthermore, TMAO is known to upregulate macrophage scavenger receptors and induce CD68 expression [169, 171], a marker known to correlate with cognitive impairment in rodents [172].

High circulating TMAO may also promote neuroinflammation, a recognised mediator of cognitive ageing and neurological function [173, 174], by increasing brain NF-κB and proinflammatory cytokines, thereby promoting proinflammatory signalling pathways [164]. Brunt and colleagues suggested that elevated TMAO in plasma and the brain can stimulate astrocytes, neuroinflammation and reduce cognitive function, especially in the subdomain of memory [164]. High circulating concentrations of TMAO also downregulated the antioxidant enzyme methionine sulfoxide reductase A in the hippocampus of aged rats with induced cognitive impairment by sevoflurane exposure [175]. This downregulation is suggested to sensitise the hippocampus to oxidative stress, promoting microglial mediated neuroinflammation and cognitive impairment. Collectively, studies indicate a detrimental effect of TMAO when modulated above physiologically relevant concentrations.

In line with this, reducing TMAO has been shown to alleviate cognitive impairment. 3,3-Dimethyl-1-butanol, an inhibitor of microbial TMA formation, reduced cognitive decline, long term potentiation and pathological deterioration in AD transgenic mice [162]. Similarly, the probiotic L. Plantarum decreased circulating TMAO levels, alleviating cognitive impairments and pathological deterioration, exhibiting the potential modulation of the gut microbiome for therapeutic benefit [176].

In contrast to the substantial evidence supporting a detrimental effect of TMAO upon the brain, several studies suggest TMAO may exert a neuroprotective effect when within normal physiological ranges (plasma levels ~ 0.5–5 µM). Hoyles and colleagues, using a mixed in vitro endothelial cell culture and in vivo rodent model approach, discovered that TMAO can enhance and protect BBB integrity through modulation of the actin cytoskeleton and tight junctions [177]. Here, administering TMAO reduced paracellular permeability, likely due to an increase in annexin A1 expression. TMAO, therefore, may promote BBB function and help protect the brain from an influx of cytotoxic molecules. Interestingly, TMA, the precursor to TMAO, was found to have a deleterious effect on endothelial barrier integrity in rodents, inducing actin stress fibre formation and leading to increased presence in the CNS [178].

TMAO is a naturally occurring osmolyte and as such has been found to stimulate TAU-induced tubulin assembly in vitro [179]. TMAO, therefore, can promote and enhance microtubule assembly in hyperphosphorylated and most mutant TAU proteins, decreasing microtubule disassembly and neuronal death; two hallmark features of AD [180]. TMAO overcomes functional deficits caused by phosphorylation by lowering the critical concentration of tubulin required for assembly [181], with assembly occurring at a faster rate than wild-type TAU [180]. Therefore, as an osmolyte, and with its ability to favourably hydrate partially denatured proteins, TMAO has been suggested as a potential therapeutic approach in AD and other protein misfolding conditions [182].

Collectively, it seems plausible that TMAO affects the brain in a dose-dependent manner, as within a physiologically relevant range, TMAO possess neuroprotective potential. However, interpreting the relationship between systemic TMAO and cognition is further complicated by studies indicating wide inter and intra-individual variations in circulating TMAO levels [183]. TMAO concentrations vary with age [184], diet [169] and cholic acid levels (a BA known to induce FMO3 expression via FXR activation [185]); factors often not accounted for in association studies. In fact, plasma TMAO concentrations have been found to mirror an individual’s intake of whole grain, fish and vegetables [186]. TMAO levels are also influenced by renal clearance, as glomerular filtration rate is inversely related to plasma TMAO concentrations [159]. As a result, changes in plasma TMAO may be a consequence of an accumulation of factors unrelated to cognitive decline [187].

TMAO as a risk factor of cognitive decline

Due to TMAO’s high association with atherosclerosis and cardiovascular disease, TMAO has been considered a risk factor of vascular dementia [188]. However, a data-driven, hypothesis-free computational analysis into microbial metabolites and AD identified TMAO as one of the top potential biomarkers of neurodegeneration, successfully predicting changes in memory and fluid cognition in ageing individuals [189]. These results show promising potential for use of TMAO as a risk factor of cognitive decline. However, the current contrasting evidence surrounding the relationship necessitates further in vivo investigation.

Amino acid-microbiota-derived metabolites

Tryptophan

Tryptophan is an essential aromatic amino acid that cannot be synthesised by animal cells [190]. Humans, therefore, need to attain tryptophan through dietary sources such as fish, milk and chicken or, if vegetarian, seeds, soybeans and peas [191, 192]. Tryptophan is a biosynthetic precursor to numerous microbial and host metabolites, making it essential to human health [190]. Approximately 4–6% of tryptophan reaches the colon where gut microbiota metabolise it into a wide variety of molecules (Fig. 2), thereby limiting the availability of tryptophan for the host [193]. Evidence for the involvement of microbiota in tryptophan metabolism comes from GF mice, who display increased plasma tryptophan levels which are normalised after conventionalisation [62, 194].

Previous experimental reports implicate tryptophan and its derivatives in modulating human health and neurological function [195]. Gut microbiota can directly and indirectly modulate two major tryptophan metabolism pathways, the serotonin pathway and the kynurenine pathway (KP), affecting the concentration of various cognitively relevant metabolites and neurotransmitters [196,197,198]. Conversely, the two pathways can negatively influence microbial proliferation and diversity [199]. Gut microbiota can also directly metabolise tryptophan into indole and its derivatives [200], which has also been associated with cognitive function [191].

The kynurenine pathway and cognitive decline

Around 90–95% of dietary tryptophan is metabolised by the KP, mainly taking place in the liver, forming the intermediates kynurenic acid, quinolinic acid, picolinic acid, 3-hydroxykynurenine (3-HK) and nicotinamide adenine dinucleotide, known as kynurenines [201]. Only tryptophan, 3-HK and kynurenine are known to readily cross the BBB. However, fluctuations in the systemic concentrations of these metabolites directly impacts KP metabolism in the CNS, including the synthesis of kynurenic acid and quinolinic acid in the brain [202]. Quinolinic acid, an endogenous neurotoxin, is known to activate N-methyl-D-aspartate (NMDA) receptors, increase neuronal activity, elevate intracellular calcium concentrations and modulate BBB integrity [203]. Quinolinic acid can also increase neuronal glutamate release whilst inhibiting its reuptake by astrocytes and inhibiting glutamate synthetase synthase (an enzyme playing a crucial role in the glutamate metabolism in astrocytes) to produce a cytotoxic response [204, 205]. Kynurenic acid, on the other hand, plays a neuroprotective role against quinolinic acid’s toxicity, acting as an antagonist on both glycine and glutamate modulatory sites of NMDA receptors at high and low concentrations respectively [198]. However, the abnormal build-up of kynurenic acid can induce glutamatergic hypofunction, possibly disturbing cognitive functioning [205].

Accumulating evidence implicates the KP in AD progression and inflammatory responses [206]. Increased plasma concentrations of the cytotoxic quinolinic acid (from 192 to 334 nM) and reduced concentrations of tryptophan (from 29.83 mM to 22.09 mM) and neuroprotective kynurenic acid (from 30.94 nM to 20.85 nM) has been associated with AD patients in comparison to healthy controls [207]. Unbalanced upregulation of the KP may trigger a degree of injury to the surrounding tissues, playing a role in neurodegeneration [208]. Previous studies have found an inverse relationship between KP activation and cognitive performance [209].

In a cognitively healthy population, increased inflammatory markers are related to poor cognitive performance [210]. In AD, indoleamine 2, 3-dioxygenase (IDO), the enzyme responsible for catabolising tryptophan into products that enter the KP, is stimulated through proinflammatory cytokine activity, including interferon-gamma (IFN-γ) [211], interleukin-12 (IL-12), interleukin-18 (IL-18) [212], and the Aβ 1–42 fragment [213]. Complex neuroinflammation in the CNS is linked with AD development. Microglia and astrocytes, which contain all of the enzymes necessary for the KP, are the primary effectors of neuroinflammation in AD [214]. The edge of senile plaques in the hippocampus of post-mortem AD brain tissue has the greatest amounts of IDO and quinolinic acid expressed by microglia and astrocytes [215]. Activated microglia are the main source of quinolinic acid throughout neuroinflammation [216]. Quinolinic acid produces hyperphosphorylation of TAU in human cortical neurones, cytotoxicity in astrocytes and neurons, astrocytic activation and astrogliosis [208, 217]. Together, these studies strongly suggest the involvement of IDO and KP metabolism in neuroinflammation and cognitive impairment.

Accordingly, the KP is a well-rationalised therapeutic target for improving cognition. Several proof-of-concept studies using known KP pathway modulators, such as the kynurenine monooxygenase (KMO) inhibitor JM6, prevents spatial memory deficits, anxiety-related behaviours, and synaptic loss in APP Tg mice [218]. In addition, the IDO-1 inhibitor, coptisine, decreases the activation of microglia and astrocytes in APP/PS1 mice, preventing neuronal loss and improving cognitive function [208]. However, the specific relationship between tryptophan depletion or supplementation and the modulation of KP intermediates remains unclear [219,220,221].

Serotonin pathway and cognitive decline

Approximately 3% of dietary tryptophan is required to produce serotonin (5-hydroxytryptamine (5-HT)) and melatonin [193]. 5-HT is primarily found in the GI tract, blood platelets and the CNS and is synthesised via a two-stage enzymatic reaction involving tryptophan hydroxylase and aromatic amino acid decarboxylase. Serotonin synthesised in the GI tract cannot cross over the BBB under healthy conditions [222]. Tryptophan, on the other hand, can enter the CNS via carrier proteins [223]. Therefore, the gut microbiota importantly regulates tryptophan availability for serotonin synthesis in the CNS.

Enzymes such as tryptophan hydroxylase and IDO balance the ratio of tryptophan metabolism via the KP and serotonin pathways [224]. A shift in tryptophan metabolism to the KP decreases the availability of tryptophan in the serotonin pathway, consequently reducing serotonin availability for the host [225]. Serotonin plays a vital role in behaviours requiring high cognitive demand [196]. Reductions in serotonin, therefore, are frequently linked with declines in learning, memory consolidation [226] and long-term memory [227]. As such, serotonin is associated with neurological disorders such as depression [228] and AD [229], resulting in treatment options such as selective serotonin reuptake inhibitors (SSRI) to increase 5-HT neurotransmission and improve mood in the context of depression. In rodents, administering tryptophan orally, thereby increasing 5-HT neurotransmission, was found to improve memory acquisition, consolidation and storage [230], whilst daily tryptophan injections improved spatial memory [231]. Together, this evidence strongly suggests a link between cognitive decline and tryptophan through changes in tryptophan metabolism.

Other tryptophan metabolites

Numerous studies have identified abnormal tryptophan metabolism in patients with cognitive decline [71, 191, 232]. Although most studies link this association with the KP and its intermediates, other tryptophan metabolites, such as indole and its derivatives, may play a role. Bacterial tryptophan catabolites tryptamine, skatole, indole, indole-3- acetic acid (IAA), indole-3- acrylic acid (IA), indole-3-aldehyde (IAld), indole propionic acid (IPA), indoxyl-3-sulfate (I3S) and indole-3-lactic acid (ILA) are ligands of the aryl hydrocarbon receptor (AhR) [233,234,235,236,237,238]. AhR is a transcription factor widely expressed by cells in the immune system and known to play a role in inflammation, a factor highly associated with ageing and cognitive decline [239]. Antibiotic-treated mice administered with indole, I3S, IPA and IAld were found to have reduced CNS inflammation via AhR activation in astrocytes [240]. Wei and colleagues discovered activation of the AhR by indole could promote neurogenesis in the adult mouse hippocampus [241]. Interestingly, this result was found to be ligand specific as kynurenine, another known AhR ligand, failed to replicate these findings.

Both in vitro and in vivo studies have associated indoles with enhancing intestinal barrier function by increasing gene expression associated with the maintenance of epithelial cell structure and function [242, 243], thereby decreasing the concentration of neuroactive products in circulation [79]. The activation of AhR also helps preserve epithelial barrier function by maintaining tight junction integrity [244]. IA may also have anti-inflammatory and anti-oxidative effects in LPS-activated human peripheral blood mononuclear cells (PBMCs) by reducing IL-6 and IL-1β secretion and activation of the NRF2-ARE pathway [245], a pathway suggested to ameliorate cognitive deficits [246, 247].

Tryptophan & derivatives as risk factors of cognitive decline

Although no research studies to date have exclusively investigated the use of tryptophan and its derivatives as a risk factor of cognitive decline, many reports have highlighted the potential use of tryptophan pathway imbalances to reveal signs of early cognitive decline [248]. Kaddurah-Daouk and colleagues concluded from studying CSF of AD patients that changes in tryptophan, as well as methionine, tyrosine, and purine metabolism occurred in MCI and AD, suggesting its potential use as a risk factor of cognitive decline [232]. However, the authors concluded that these changes may not be detectable in plasma, as the amount to which metabolic changes in blood mirror fluctuations in CSF remains to be investigated. Nevertheless, plasma metabolic profiling revealed changes in tryptophan metabolism in early cognitive decline, along with alterations in progesterone, lysophosphatidylcholine, L-phenylalanine, dihydrosphingosine and phytosphingosine [248]. Despite a lack of studies into the use of tryptophan and its derivates as a risk factor of cognitive decline, these studies highlight the possible future use of metabolomic profiling to detect early changes.

GABA

Through either direct access via the circulatory system, or via other communication routes, microbial metabolites may have the capacity to interfere and impact the function of the CNS [249, 250]. GABA is the main inhibitory neurotransmitter in the human brain and other parts of the body [251] and is reportedly unable to cross the BBB, although this statement is disputed [252]. This molecule was recently shown to be both a product of bacteria in the gut [250, 253, 254] and an important substrate for other gut community members [255]. It was also shown to have activity in rodent models of anxiety and visceral pain [256]. Bacterial strains, such as L. rhamnosus, can also modify GABA receptor expression and concentrations of glutamate (a precursor to GABA) and GABA in the brain [257].

Other bacterial amino acid metabolites

Amino acids present in dietary protein serve (particularly if overconsumed) as a fermentation substrate for bacteria in the large intestine. P—Cresol is the product of the microbial conversion of tyrosine, notably by the bacteria from the Coriobacteriaceae or Clostridium genera [258]. P—Cresol is a known uremic toxin and therefore can be further conjugated with sulphate by host cells to form p—cresyl sulphate (PCS) as part of the detoxification mechanism, promoting the removal of the metabolite by the kidneys.

P—Cresol is known to increase endothelial permeability in vitro through modulation of the actin cytoskeleton and adherens junctions [259], decreasing the gut’s barrier function. In the brain, p-cresol has been found to modulate dopamine turnover in Autism Spectrum Disorder BTBR mice, significantly increasing anxiety-like and hyperactive behaviours [260]. p-Cresol’s derivative, PCS, has been detected in the CSF of PD patients, suggesting the metabolite may cross the BBB and have a pathogenic effect in the CNS [261]. Although, this relationship may in part be due to the increased permeability of the BBB seen in PD [262]. PCS has been linked with cell death and dysfunction through oxidative stress, inflammation, impairment of mitochondrial dynamics and vascular disruption [263,264,265,266]. Moreover, PCS administration in mice with nephrectomy contributed to neurological dysfunction through impairment of cell survival and neurogenesis, supporting its potential role in cognitive decline [267].

Imidazole propionate (ImP) has recently been uncovered as a microbially produced metabolite derived from the amino acid histidine [268]. Elevated serum concentrations of ImP are associated with low bacterial gene richness [269], a factor previously linked to low-grade inflammation, metabolic and inflammatory disorders [270]. ImP is also associated with a type 2 diabetes-related microbiome, stimulating impaired glucose metabolism through the initiation of the p38γ-mTOR1-S6K1 signalling pathway [268, 269, 271]. Type 2 diabetes is a well-characterised risk factor for dementia, with a 1.5–2.5-fold increase in dementia risk, suggesting an association between ImP, the gut microbiome and cognitive decline [272, 273].

Other emerging microbial-derived metabolites

During digestion, nutrients and bioactives (proteins, amino acids, polysaccharides, fibres, fats, polyphenols, etc.) are catabolised into host-derived and bacterial metabolites that have the ability to interact with the host’s cells and the resident gut microbiome [256, 274]. This continuous process results in the production of a wide array of chemicals representing a wealth of chemical classes. Dietary proteins are broken down into potentially active peptides [256] that are further transformed into bacterial products such as neurotransmitter amino acids like glutamate, glycine, aspartate, serine and GABA or polyamines [250, 275, 276]. Aromatic amino acids (tryptophan, tyrosine, and phenylalanine) and polyphenols yield a myriad of compounds during catabolism leading to the formation of simpler structures containing at least one phenol ring (phenols) which can then be further transformed by the host (sulfation, glucuronidation) before re-entering circulation [256, 274]. Additionally, dietary choline and niacin are substrates for the synthesis of molecules essential for cellular function in the brain namely acetylcholine and nicotinamide adenine dinucleotide (NAD +) precursors [277,278,279], some of which have recently been shown to be synthesised by the gut microbiota [250, 254, 275, 278, 280]. These recent developments provide further evidence of the microbiota’s role in the production of beneficial signalling molecules that contribute to the maintenance of homeostasis during the ageing process.

As described earlier in the review, the BBB selectively allows circulating solutes to enter the CNS. Polyamines, polyphenols and some of their products (3-(3’-hydroxyphenyl)propionate and 3-hydroxybenzoate) [281] have been shown to cross the barrier even though the transfer seems somewhat limited [282,283,284,285,286]. Meanwhile, nicotinamide and niacin, both precursors for NAD + , a coenzyme essential for the maintenance of the CNS, have the capacity to freely cross the BBB [278, 287]. More research on the topic is needed as the knowledge regarding their transport across BBB is in its infancy and partly based on in vitro models [282, 286, 288]. The question of whether the potential activity of those molecules on brain functions is either direct or based on interactions with peripheral systems remains open [289].

Short-chain fatty acids

Short-chain fatty acids (SCFAs) are small organic compounds primarily formed from microbial anaerobic fermentation of dietary fibres in the cecum and colon [290]. Accumulating evidence suggests SCFAs can attenuate cognitive decline, however, the underlying mechanisms remain unclear [291]. Recent studies suggest SCFAs can cross the BBB via monocarboxylate transporters present in endothelial cells within the brain tissue [292]. In fact, the uptake of SCFAs into the brain has formerly been exhibited in rodents following the injection of 14C-SCFAs into the carotid artery [293]. However, as well as crossing the BBB, SCFAs may also help preserve its integrity. GF mice with reduced SCFA levels were found to exhibit increased BBB permeability due to a reduction in the expression of tight junction proteins [294]. This BBB dysfunction was later reversed following conventionalisation with pathogen-free microbiota and monoculture strains producing SCFAs. Furthermore, in a rodent model of traumatic brain injury, the administration of sodium butyrate prevented BBB breakdown and promoted neurogenesis, highlighting a key role for SCFAs in not only maintaining CNS homeostasis but also possibly in preventing or reducing neural decline [295].

Select SCFAs can also manipulate epigenetic mechanisms, including DNA methylation, histone modification and their interactions, which may influence age-related cognitive changes [296]. Butyrate has been widely investigated due to its roles in receptor signalling and metabolic regulation. However, pharmacological studies also highlight butyrate as a histone deacetylase inhibitor, capable of increasing histone acetylation and inducing the expression of neurotrophic and anti-inflammatory genes [297, 298]. Accumulating evidence also suggests a role for butyrate in modifying DNA methylation [299,300,301].

In the CNS, SCFAs have also been linked to reducing neuroinflammatory processes important for shaping brain function. Sodium butyrate has been linked to a decrease in microglial activation and pro-inflammatory cytokine secretion [297, 302]. Rodents supplemented with dietary acetate had a decrease in neuroglial activation by reducing the expression of pro-inflammatory cytokines and modulating brain histone acetylation [303]. Likewise, acetate also modulated inflammatory cytokines and signalling pathways in astrocyte primary culture [304]. In vivo and in vitro sodium butyrate administration was observed to have an anti-inflammatory role via protein kinase B (Akt)-RhoGTPase signalling and histone deacetylase inhibition, stimulating structural and functional changes in microglial towards a homeostatic profile [305]. SCFAs may also improve brain hypometabolism, a known contributor to neuronal dysfunction and AD, by providing an alternate substrate for energy metabolism [306, 307] highlighting a further potential method to mitigate and protect against neuroinflammatory processes. Nevertheless, the precise signalling underlying SCFA's influence within the CNS remains unclear, however, the inhibition of histone deacetylase has been put forward as the primary mechanism [308].

Select SCFAs may also moderate AD progression [309]. For example, valeric acid, butyric acid and propionic acid have been found in vitro to interfere with protein–protein interactions necessary for Aβ assemblies, potentially reducing the formation of toxic aggregates [290]. Yet, it remains unclear if SCFAs produced in the GI tract can play a role in protein misfolding in vivo [290]. However, Colombo and colleagues found GF AD mice display reduced circulatory SCFA concentrations and Aβ deposition, yet when supplemented with SCFAs, show an increase in Aβ plaque deposition, suggesting SCFA mediation [309]. In line with this, a clinical study into elderly individuals with ranging cognitive performance found an association between SCFA levels in the blood and brain amyloid deposition [310].

APOE genotype, the largest genetic risk factor of AD, has been associated with the composition of butyrate-producing microbiota in the gut [311]. Faecal samples from AD patients typically consist of an abundance of SCFAs, particularly butyrate-producing bacteria [312]. However, currently, there is no comparison of SCFA concentrations in age-matched healthy controls and therefore its use as a risk factor of cognitive decline is limited. This may in part be due to SCFA's volatile nature, making the compound difficult to detect in human samples, and current research also demonstrating low reproducibility. Notably, participant diet is rarely incorporated when quantifying SCFAs in research studies. Yet, the quantity and type of ingested fibre are known to have a large influence on microbial composition and, therefore, the concentration and type of SCFAs produced [306, 313]. Faecal SCFA concentrations also cannot fully signify production rates or accurate concentrations of SCFAs present in the colon, as significant percentages of SCFAs are immediately consumed locally in the gut [314, 315]. Changes in SCFA faecal concentrations, therefore, may be the result of either a fluctuation in its production or colonic absorption. Consequently, as of present, the knowledge on using SCFAs as a risk factor of cognitive decline is extremely limited.

Acetylcholine

Acetylcholine (ACh) is a common cholinergic neurotransmitter in the central and peripheral nervous systems. In the periphery, ACh can be produced from choline by numerous bacteria, including Lactobacillus plantarum, Bacillus subtilis, Escherichia coli, and Staphylococcus aureus [316, 317]. Within the microbiota-gut-brain axis, ACh can modulate intestinal motility, secretion and enteric neurotransmission. essential for the transmission of excitatory signals between neurons. Its dysregulation is closely linked with AD [318]. ACh cannot cross the BBB. Therefore, choline availability in the periphery importantly modulates the concentration of ACh in the CNS [319].

Dopamine

Dopamine is the leading catecholamine neurotransmitter in the mammalian CNS, playing a key role in a broad spectrum of cognitive abilities, including working memory, planning, selective attention abilities, motivation and reward processing [320, 321]. Dopaminergic transmission abnormalities have been linked to cognitive decline and numerous CNS disorders [reviewed by [322]]. Dopamine itself cannot cross the BBB. However, its precursor molecule L-3,4-dihydroxyphenylalanine (L-DOPA) can be transported across the BBB by large neutral amino acid transporters (LAT1) expressed on endothelial cells [323].

One approach to investigating the involvement of gut microbiota and their metabolites on cognitive decline is through the use of broad-spectrum antibiotics to induce gut dysbiosis by preventing the growth of select microorganisms. Administering an antibiotic cocktail of ampicillin, vancomycin, neomycin, metronidazole, and amphotericin B to the drinking water of male Swiss mice increased concentrations of L-DOPA and homovanillic acid (HVA), a dopamine-derived metabolite, in the amygdala in comparison to control mice [66]. However, no significant changes in dopamine levels were detected. Similarly, Hoban and colleagues observed increased concentrations of L-DOPA in the prefrontal cortex and hippocampus of adult male Sprague–Dawley rats after supplying an antibiotic cocktail of ampicillin, vancomycin, ciprofloxacin, imipenem, and metronidazole for 42 days. Together, these studies suggest antibiotic-induced dysbiosis can impact dopamine neurochemistry in the rodent brain.

As discussed earlier in this review, one mechanism in which intestinal bacteria can communicate with the brain is via stimulation of the vagus nerve. Interestingly, Han and colleagues found stimulation of vagal afferent fibres from the upper intestinal tract can promote dopamine release in the brain of mice [324]. Dopamine can also be synthesised in the intestinal lumen by gut microbes [325]. Indeed, gut microbes belonging to the genus Prevotella, Bacteroides, Lactobacillus, Bifidobacterium, Clostridium, Enterococcus, and Ruminococcus have been suggested to modulate dopaminergic activity and influence Parkinson’s disease (PD) pathophysiology (reviewed by [326]). Gut microbiota can also increase luminal dopamine bioavailability through enzymes such as β- glucuronidase [325] and tyrosine decarboxylase [327], demonstrating a key role of the gut microbiota in modulating peripheral dopamine levels. Interestingly, plasma L-DOPA levels were found to be significantly increased in probable AD patients in comparison to controls, whereas dopamine concentrations were decreased [328].

Polyphenols

Both plant-based foods, rich in polyphenols, and dietary proteins are substrates for colonic bacteria which produce phenolic compounds that potentially benefit human health [256, 274, 329,330,331]. The current research on the impact of beneficial and harmful microbial phenolic compounds 3-(3’-hydroxyphenyl) propionate, 3-hydroxybenzoate, indoxyl sulfate, p-cresol sulfate on the brain is at an early stage but determining the role of those products on the gut-brain axis is a promising field of research [256, 274, 281, 330]. Frolinger and colleagues have recently demonstrated a link between polyphenolic products produced by gut microbiota and cognitive resilience in rats [332] and Esteban-Fernández et al. showed that 3-hydroxyphenylacetic acid and other microbial-derived phenolic compounds have a neuroprotective effect on a human neuroblastoma cell line [333]. Metabolomics on circulating metabolites also correlated levels of catabolites of the phenylalanine and tyrosine pathways to poorer mini-mental state examination (MMSE) scores in a cohort of hypertensive patients [334]. Mostly driven by in vitro and animal-based studies, research on the effect of phenolic compounds are nonetheless accruing evidence that microbial phenolic compounds could play a role in brain metabolism [286].

Polyamines

Polyamines were first described in 1677 by Antonie van Leewenhoek who reported the presence of crystals in human semen [284]. It was much later in 1924 that Dudley and colleagues characterised one of their components, isolating spermine from bovine brain [284]. Polyamines are small molecules essential to cell growth and ubiquitous to all life forms. Most of the polyamine pool is bound to RNA conferring an important role to polyamines in stabilising this molecule and contributing to the process of its translation [284]. Putrescine, spermidine and spermine are synthesized by plants, mammals and bacteria and represent the most abundant polyamines found in tissues [335,336,337].

Levels of polyamines found in mice decline with brain ageing [65, 338] but in humans, only spermidine levels seem to change over time reaching their highest level at 40 years of age and remaining at similar levels thereafter [336]. Elevated levels have been reported in the brain from AD patients, where increased ornithine decarboxylase activity was found to be associated with AD processes [339].

They are abundant in food, quickly absorbed and distributed to all body tissues [340]. The polyamine content in the lower part of the intestine however is considered to be mostly of microbial origin [337]. Sustained circulating levels at an older age have been associated with enhanced longevity and the prevention of age-associated disease [340, 341]. Conversely, lower spermidine levels were found in blood from AD patients when compared to healthy individuals [342], a characteristic that was associated with lower MMSE scoring in another study conducted on older subjects in nursing homes [343].

Preserving adequate levels of polyamines could represent a valuable approach to maintaining the optimal functioning of cell metabolism and the prevention of chronic illnesses. Supplementation could be achieved by a regular intake of a polyamine-rich food diet or synthetic polyamines, or by the provision of microbial polyamine synthesis with probiotic supplements [344]. A recent study highlighted olive oil, fruits, cheese, and seafood as good sources of polyamines and that a steady intake may have a role in prolonging human life. The authors speculated that the mechanism involved could be a capacity for polyamines to counteract mild chronic inflammation and confer beneficial effects on vascular function [340]. Another study reported an association between spermidine intake estimated with a self-reported food frequency questionnaire and cortical thickness and hippocampal volume in older adults [345].

A study on mice fed arginine, a precursor for the synthesis of polyamines [276, 337] and probiotics LKM512 showed that long term administration offered protection against age-induced memory impairment via a mechanism involving the production of polyamines by microbiota [341]. The putative protective properties of polyamines are inhibition of cytokines release, inhibition of reactive oxygen species (ROS) production [346, 347], an impact on T-cell function and the maintenance of synaptic plasticity through the prevention of demyelination [347], thus presenting a defence against events that embody hallmarks of neurodegeneration [348, 349]. Polyamines also have the capacity to induce cytoprotective autophagy, a process involving the degradation of damaged organelles and biological debris [344, 350, 351]. They have a significant role in the maintenance of mitochondrial metabolic function. Indeed, spermidine is needed to chemically modify eukaryotic initiation factor 5A (eIF5A), an important enzyme involved in TCA cycle maintenance and electron transport chain in macrophages [352], highlighting an important role for this polyamine in the regulation of mitochondrial metabolism as any reduced activity can lead to neuroinflammation and neurodegeneration [348, 349].

As mentioned earlier, host bacterial production of polyamines was recently shown to delay senescence in mice [341]. Although the exact mechanisms were not elucidated, the authors speculated that autophagy [350, 351] may play a role in the preservation of memory capacity in ageing. This is further reinforced by recent studies on mice which showed that supplementation by spermidine and spermine may delay brain ageing and alleviate AD pathology via mechanisms involving autophagy, promotion of ATP, reduction of ROS [353, 354] and inflammation [355]. Maglione and colleagues showed that spermidine offered protection from synaptic alterations in the hippocampus of ageing mice extending their lifespan with a late treatment (starting at 18 months) [356].

The research on both autophagy and polyamines and cognitive health, which is getting traction, has recently translated into human trials. A long-term spermidine-rich treatment (dosage: 1.2 mg/day) was given to participants at risk of developing AD and found to be safe and well-tolerated [357]. This 3‐month randomized, placebo-controlled, double‐blind Phase II trial was shown to moderately improve the memory performance and to enhance the mnemonic discrimination ability of the treated individuals compared to the placebo-treated group [358]. The authors have designed a new trial using the same treatment that will expand the intervention period to 12 months and will include a larger cohort (n = 100 as opposed to n = 30) and a follow-up assessment 18 months after the start of the study [359]. In parallel, another group supplied older adults in nursing homes with spermidine added to bread for 3 months and evaluated the cognitive performance of the subjects with the CERAD-Plus test which consists of seven tests including an MMSE, a learn, recall and recognize a word list and phonemic fluid [360]. They reported a significant correlation between an intake of spermidine and improvement in cognitive performance, particularly in subjects with mild and moderate dementia. Their preliminary results offer hope for the possible mitigation of cognitive decline by enabling sustainable levels of polyamines in the body.

Nicotinamide

Energy and niacin and nicotinamide pathways are under tight homeostasis as shown by a lack of change in ATP and nicotinamides levels in the brain of colonised ex germ-free mice [65]. There is evidence that the levels of these molecules which are essential for the development and maintenance of CNS neurons decline with age and in neurogenerative states [277]. Promising results from an AD animal model led to a 24-week double-blind, placebo-controlled randomized clinical trial of nicotinamide in subjects with mild to moderate AD [279]. Unfortunately, this study failed to show an improvement in cognitive function in those volunteers. A similar study provided a 10-week supplementation with nicotinamide riboside (NR) to older individuals with MCI [361]. This trial resulted in demonstrating a positive effect on certain functions in the brain and frailty measures but like in the previous study, ultimately ended in a lack of change in cognitive measures [361]. This illustrates the complexity of translating results from animal studies to human trials with the dose, duration of the supplementation and environmental factors affecting the likelihood of a successful outcome. Nonetheless, recent studies showed that the gut microbiota can assist in the production of nicotinamide and other NAD + precursors [254] as demonstrated by Kim and colleagues who showed that treatment with nicotinamide mononucleotide in mice not only led to the microbial production of the deamidated product nicotinic acid mononucleotide, but also tripled the endogenous levels of NR, showing an important connection between the gut microbiome and the niacin and nicotinamide pathway [280].

Vitamin K

Vitamin K is a vital micronutrient that can be derived directly from our diet (phylloquinone) or intestinal microbiota (menaquinone) [362]. Vitamin K’s role is well-defined in blood coagulation and its beneficial effects on myelin integrity in the brain [363, 364]. Recent studies outline a positive relationship between vitamin K levels and cognitive performance [365, 366], and the administration of vitamin K antagonists to rats alters cognitive performance [367]. Increased dietary vitamin K intake is linked to a decrease in subjective memory complaints in an elderly cohort [368], whilst low concentrations of vitamin K in the blood have been correlated with the APOE-ε4 allele; the largest genetic risk factor of AD [363]. However, the direct relationship between microbial-derived vitamin K and cognition, and hence its use as a risk factor of cognitive decline, is yet to be uncovered.

Conclusions and future directions

The concept of microbial-derived metabolites influencing cognitive decline is gaining traction, with implications in the field of neuroscience, metabolomics and hepatology. However, due to the complexity of this relationship, the specific myriad of mechanisms responsible remain largely unknown, whilst defined roles of individual metabolites are only characterised for a select few (for a summary see Fig. 3). Therefore, amid this ambiguity, there remains a real need for additional research to highlight and validate key pathways, metabolites and mechanisms to further elucidate the influence of the microbiota-gut-brain axis on cognition [189].

Fig. 3
figure 3

Key potential pathways through which microbial-derived metabolites influence cognitive function. An illustration of the main underlying mechanisms linking microbial metabolites and the brain. Dietary-derived precursor molecules can be metabolised by gut microbiota to form bioactive metabolites. These microbial-derived metabolites can influence gut permeability, blood–brain barrier function, neuroinflammation, vagus nerve activation, neurogenesis and excitotoxicity affecting the regulation of the microbiota-gut-brain axis and cognitive function. The green colour highlights a protective and beneficial effect, whereas red indicates a detrimental effect. Acronyms: BBB: blood–brain barrier; DCA: deoxycholic acid; ECC: enterochromaffin cells; FMO: flavin-containing monooxygenase; GABA: γ-aminobutyric acid; IA: indole-3- acrylic acid; IAA: indole-3- acetic acid; IAld: indole-3-aldehyde; ILA: indole-3-lactic acid; I3S: indoxyl-3-sulfate; KYNA; kynurenic acid; LCA: lithocholic acid; NMDAR: N-methyl-D-aspartate receptor; QUIN; quinolinic acid; TMA: trimethylamine; TMAO: trimethylamine N-oxide; TUDCA: tauroursodeoxycholic acid

There remain many challenges facing this growing field. Firstly, a lack of specificity limits our ability to distinguish between host vs microbiota-derived metabolite contribution as particularly if there is known co-metabolism, true microbial involvement may be masked or exaggerated. Secondly, as demonstrated by TMAO [362], some inconsistencies still exist among certain metabolites under context-specific vs dose-specific conditions. This may in part be due to heterogeneity between studies, with variations in study designs, methods of assessing cognitive performance and/or quantifying metabolites. As a result, further research ought to be collated via a more standardised methodology to increase comparability. Thirdly, the influence of the microbiome on cognition is not the totality of microbial metabolites produced in the gut as the varying capabilities of these metabolites to penetrate the BBB play a key role [79]. Consequently, the mechanisms used by many metabolites to cross the BBB are still unknown and some may even be synthesised de novo. Fourthly, from a translational perspective, the described research has largely been conducted in animals. Establishing whether these findings translate to humans will be crucial yet challenging due to the greater complexity and environmental exposure humans encounter, in turn shaping each individual’s microbiome [369]. Finally, understanding these highly complex systems, particularly as we move more towards human studies, requires the continued advancement of computational and statistical methods to obtain and implement multi-omics and longitudinal data necessary for a comprehensive approach [330]. Together, these challenges render it difficult to outline specific host-microbiota interactions in a mechanistic manner, which is needed to advance the field past associations towards implementable microbiota-driven targets.

Nevertheless, the wealth of association studies highlight a positive future for the use of microbiota-derived metabolites as risk factors of cognitive decline [370]. Future studies should progress using robust and replicable metabolic phenotyping across various stages of cognitive decline in humans. Recent advancements using this approach are underway, utilising metabolic phenotyping of urine [371] and blood [153, 372] to predict incipient AD with high degrees of accuracy. However, several studies using comparable approaches have not been able to replicate these findings [373, 374]. This may be due to intrinsic difficulties surrounding the heterogeneity of cognitive decline seen in neurodegenerative diseases and the variety of analytical methods used in metabolic profiling, ranging from 1H-NMR, LC–MS/MS, GC–MS, UHPLC-MS and CE-MS [371]. Hence, currently, the literature is too scarce to support the implementation of metabolite-derived risk factors in clinical practice.

In conclusion, although significant work remains to fully understand the role of microbial-derived metabolites as key mediators of cognitive decline, identifying modifiable factors that promote healthy ageing and cognition will have vital clinical implications in today’s growing elderly population, whilst also helping to identify novel underlying mechanism.

Availability of data and materials

Not applicable.

Abbreviations

5-HT:

Serotonin (5-hydroxytryptamine)

ACh:

Acetylcholine

AD:

Alzheimer’s disease

AhR:

Aryl hydrocarbon receptor

Aβ:

Amyloid-β

BA:

Bile acids

BBB:

Blood–brain barrier

BDNF:

Brain-derived neurotrophic factor

CA:

Cholic acid

CDCA:

Chenodeoxycholic acid

CNS:

Central nervous system

CSF:

Cerebrospinal fluid

CYP27A1:

Sterol 27-hydroxylase

CYP46A1:

Cholesterol 24-hydroxylase

CYP7A1:

Cholesterol 7α-hydroxylase

DCA:

Deoxycholic acid

DMN:

Default mode network

ECC:

Enterochromaffin cells

FMO1/3:

Flavin-containing monooxygenase 1/ 3

GABA:

γ-Aminobutyric acid

GF:

Germ-free

GI:

Gastrointestinal

GUDCA:

Glycoursodeoxycholic acid

HVA:

Homovanillic acid

IA:

Indole-3- acrylic acid

IAA:

Indole-3- acetic acid

IAld:

Indole-3-aldehyde

IDO:

Indoleamine 2, 3-dioxygenase

ILA:

Indole-3-lactic acid

ImP:

Imidazole propionate

IPA:

Indole propionic acid

I3S:

Indoxyl-3-sulfate

KP:

Kynurenine pathway

LAT1:

Large neutral amino acid transporters

LCA:

Lithocholic acid

L-DOPA:

L-3,4-Dihydroxyphenylalanine

LPS:

Lipopolysaccharide

MCI:

Mild cognitive impairment

MMSE:

Mini-mental state examination

MRI:

Magnetic resonance imaging

NMDA:

N-methyl-D-aspartate

NR:

Nicotinamide riboside

PBMCs:

Peripheral blood mononuclear cells

PCS:

p-Cresyl sulphate

PD:

Parkinson’s disease

PET:

Positron emission tomography

ROS:

Reactive oxygen species

SCFAs:

Short-chain fatty acids

TLR:

Toll-like receptor

TMA:

Trimethylamine

TMAO:

Trimethylamine N-oxide

TUDCA:

Tauroursodeoxycholic acid

References

  1. Alzheimer’s Association. Alzheimer’s disease facts and figures. Alzheimer’s & Dementia. 2019;2019(15):321–87.

    Google Scholar 

  2. Eshkoor SA, Hamid TA, Mun CY, Ng CK. Mild cognitive impairment and its management in older people. Clin Interv Aging. 2015;10:687–93.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Kelley BJ, Petersen RC. Alzheimer’s Disease and Mild Cognitive Impairment. Neurol Clin. 2007;25:577–609.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Tiwari S, Atluri V, Kaushik A, Yndart A, Nair M. Alzheimer’s disease: pathogenesis, diagnostics, and therapeutics. Int J Nanomedicine. 2019;14:5541–54.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Kivipelto M, Helkala E-L, Laakso MP, Hänninen T, Hallikainen M, Alhainen K, et al. Midlife vascular risk factors and Alzheimer’s disease in later life: longitudinal, population based study. BMJ British Medical Journal Publishing Group. 2001;322:1447–51.

    Article  CAS  Google Scholar 

  6. Balagopal PB, de Ferranti SD, Cook S, Daniels SR, Gidding SS, Hayman LL, et al. Nontraditional risk factors and biomarkers for cardiovascular disease: mechanistic, research, and clinical considerations for youth. Circulation. American Heart Association. 2011;123:2749–69.

  7. Reitz C, Tang M-X, Manly J, Mayeux R, Luchsinger JA. Hypertension and the Risk of Mild Cognitive Impairment. Arch Neurol. 2007;64:1734–40.

    Article  PubMed  PubMed Central  Google Scholar 

  8. Profenno LA, Porsteinsson AP, Faraone SV. Meta-Analysis of Alzheimer’s Disease Risk with Obesity, Diabetes, and Related Disorders. Biol Psychiat. 2010;67:505–12.

    Article  PubMed  Google Scholar 

  9. Moheet A, Mangia S, Seaquist E. Impact of diabetes on cognitive function and brain structure. Ann N Y Acad Sci. 2015;1353:60–71.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Knopman D, Boland LL, Mosley T, Howard G, Liao D, Szklo M, et al. Cardiovascular risk factors and cognitive decline in middle-aged adults. Neurology. Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. 2001;56:42–8.

  11. Dye L, Boyle NB, Champ C, Lawton C. The relationship between obesity and cognitive health and decline. Proceedings of the Nutrition Society. Cambridge University Press. 2017;76:443–54.

  12. Goldstein FC, Ashley AV, Endeshaw Y, Hanfelt J, Lah JJ, Levey AI. Effects of Hypertension and Hypercholesterolemia on Cognitive Functioning in Patients with Alzheimer’s Disease. Alzheimer Dis Assoc Disord. 2008;22:336–42.

    Article  PubMed  PubMed Central  Google Scholar 

  13. Livingston G, Huntley J, Sommerlad A, Ames D, Ballard C, Banerjee S, et al. Dementia prevention, intervention, and care: 2020 report of the Lancet Commission. Lancet. 2020;396:413–46.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Nutaitis AC, Tharwani SD, Serra MC, Goldstein FC, Zhao L, Sher SS, et al. Diet as a Risk Factor for Cognitive Decline in African Americans and Caucasians with a Parental History of Alzheimer’s Disease: A Cross-Sectional Pilot Study Dietary Patterns. J Prev Alzheimers Dis. 2019;6:50–5.

    CAS  PubMed  Google Scholar 

  15. Gareau MG. Microbiota-Gut-Brain Axis and Cognitive Function. In: Lyte M, Cryan JF, editors. Microbial Endocrinology: The Microbiota-Gut-Brain Axis in Health and Disease. New York, NY: Springer; 2014. p. 357–71.

    Chapter  Google Scholar 

  16. Berg G, Rybakova D, Fischer D, Cernava T, Vergès M-CC, Charles T, et al. Microbiome definition re-visited: old concepts and new challenges. Microbiome. 2020;8:103.

  17. Chelakkot C, Ghim J, Ryu SH. Mechanisms regulating intestinal barrier integrity and its pathological implications. Exp Mol Med Nature Publishing Group. 2018;50:1–9.

    Article  CAS  Google Scholar 

  18. Mayer EA, Knight R, Mazmanian SK, Cryan JF, Tillisch K. Gut Microbes and the Brain: Paradigm Shift in Neuroscience. J Neurosci. 2014;34:15490–6.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Bonaz B, Bazin T, Pellissier S. The Vagus Nerve at the Interface of the Microbiota-Gut-Brain Axis. Front Neurosci. 2018;12:49.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Donaldson GP, Lee SM, Mazmanian SK. Gut biogeography of the bacterial microbiota. Nat Rev Microbiol. 2016;14:20–32.

    Article  CAS  PubMed  Google Scholar 

  21. Donaldson GP, Lee SM, Mazmanian SK. Gut biogeography of the bacterial microbiota. Nat Rev Microbiol Nature Publishing Group. 2016;14:20–32.

    Article  CAS  Google Scholar 

  22. Rothschild D, Weissbrod O, Barkan E, Kurilshikov A, Korem T, Zeevi D, et al. Environment dominates over host genetics in shaping human gut microbiota. Nature Nature Publishing Group. 2018;555:210–5.

    CAS  Google Scholar 

  23. Ling Z, Zhu M, Yan X, Cheng Y, Shao L, Liu X, et al. Structural and Functional Dysbiosis of Fecal Microbiota in Chinese Patients With Alzheimer’s Disease. Frontiers in Cell and Developmental Biology. 2021;8: 634069.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Liu S, Gao J, Zhu M, Liu K, Zhang H-L. Gut Microbiota and Dysbiosis in Alzheimer’s Disease: Implications for Pathogenesis and Treatment. Mol Neurobiol. 2020;57:5026–43.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Li B, He Y, Ma J, Huang P, Du J, Cao L, et al. Mild cognitive impairment has similar alterations as Alzheimer’s disease in gut microbiota. Alzheimer’s & Dementia. 2019;15:1357–66.

    Article  Google Scholar 

  26. Liu P, Wu L, Peng G, Han Y, Tang R, Ge J, et al. Altered microbiomes distinguish Alzheimer’s disease from amnestic mild cognitive impairment and health in a Chinese cohort. Brain Behav Immun. 2019;80:633–43.

    Article  PubMed  Google Scholar 

  27. Zhang X, Wang Y, Liu W, Wang T, Wang L, Hao L, et al. Diet quality, gut microbiota, and microRNAs associated with mild cognitive impairment in middle-aged and elderly Chinese population. Am J Clin Nutr. 2021;114:429–40.

    Article  PubMed  Google Scholar 

  28. Nagpal R, Neth BJ, Wang S, Mishra SP, Craft S, Yadav H. Gut mycobiome and its interaction with diet, gut bacteria and alzheimer’s disease markers in subjects with mild cognitive impairment: A pilot study. EBioMedicine. 2020;59: 102950.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Saji N, Murotani K, Hisada T, Tsuduki T, Sugimoto T, Kimura A, et al. The relationship between the gut microbiome and mild cognitive impairment in patients without dementia: a cross-sectional study conducted in Japan. Sci Rep. Nature Publishing Group. 2019;9:19227.

  30. Bostanciklioğlu M. The role of gut microbiota in pathogenesis of Alzheimer’s disease. J Appl Microbiol. 2019;127:954–67.

    Article  PubMed  Google Scholar 

  31. Visconti A, Le Roy CI, Rosa F, Rossi N, Martin TC, Mohney RP, et al. Interplay between the human gut microbiome and host metabolism. Nat Commun. 2019;10:4505.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Lubinski R. Dementia and communication. Singular. 1995.

  33. Murman DL. The Impact of Age on Cognition. Semin Hear. 2015;36:111–21.

    Article  PubMed  PubMed Central  Google Scholar 

  34. Mortamet B, Zeng D, Gerig G, Prastawa M, Bullitt E. Effects of Healthy Aging Measured By Intracranial Compartment Volumes Using a Designed MR Brain Database. Med Image Comput Comput Assist Interv. 2005;8:383–91.

    PubMed  PubMed Central  Google Scholar 

  35. Scahill RI, Frost C, Jenkins R, Whitwell JL, Rossor MN, Fox NC. A longitudinal study of brain volume changes in normal aging using serial registered magnetic resonance imaging. Arch Neurol. 2003;60:989–94.

    Article  PubMed  Google Scholar 

  36. Deary IJ, Corley J, Gow AJ, Harris SE, Houlihan LM, Marioni RE, et al. Age-associated cognitive decline. Br Med Bull. 2009;92:135–52.

    Article  PubMed  Google Scholar 

  37. Raz N, Rodrigue KM. Differential aging of the brain: Patterns, cognitive correlates and modifiers. Neurosci Biobehav Rev. 2006;30:730–48.

    Article  PubMed  PubMed Central  Google Scholar 

  38. Sullivan EV, Pfefferbaum A. Diffusion tensor imaging and aging. Neurosci Biobehav Rev. 2006;30:749–61.

    Article  PubMed  Google Scholar 

  39. Bolandzadeh N, Davis JC, Tam R, Handy TC, Liu-Ambrose T. The association between cognitive function and white matter lesion location in older adults: a systematic review. BMC Neurol. 2012;12:126.

    Article  PubMed  PubMed Central  Google Scholar 

  40. Alexander GE, Bergfield KL, Chen K, Reiman EM, Hanson KD, Lin L, et al. Gray matter network associated with risk for Alzheimer’s disease in young to middle-aged adults. Neurobiol Aging. 2012;33:2723–32.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Irwin K, Sexton C, Daniel T, Lawlor B, Naci L. Healthy Aging and Dementia: Two Roads Diverging in Midlife? Front Aging Neurosci. 2018;10:275.

    Article  PubMed  PubMed Central  Google Scholar 

  42. Adluru N, Destiche DJ, Lu SY-F, Doran ST, Birdsill AC, Melah KE, et al. White matter microstructure in late middle-age: Effects of apolipoprotein E4 and parental family history of Alzheimer’s disease. Neuroimage Clin. 2014;4:730–42.

  43. Persson J, Lind J, Larsson A, Ingvar M, Cruts M, Van Broeckhoven C, et al. Altered brain white matter integrity in healthy carriers of the APOE epsilon4 allele: a risk for AD? Neurology. 2006;66:1029–33.

    Article  CAS  PubMed  Google Scholar 

  44. Heise V, Filippini N, Ebmeier KP, Mackay CE. The APOE ɛ4 allele modulates brain white matter integrity in healthy adults. Mol Psychiatry. 2011;16:908–16.

    Article  CAS  PubMed  Google Scholar 

  45. Miller MI, Ratnanather JT, Tward DJ, Brown T, Lee DS, Ketcha M, et al. Network Neurodegeneration in Alzheimer’s Disease via MRI Based Shape Diffeomorphometry and High-Field Atlasing. Frontiers in Bioengineering and Biotechnology. 2015;3:54.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Thompson PM, Hayashi KM, De Zubicaray GI, Janke AL, Rose SE, Semple J, et al. Mapping hippocampal and ventricular change in Alzheimer disease. Neuroimage. 2004;22:1754–66.

    Article  PubMed  Google Scholar 

  47. Jacobs HIL, Becker JA, Kwong K, Engels-Domínguez N, Prokopiou PC, Papp KV, et al. In vivo and neuropathology data support locus coeruleus integrity as indicator of Alzheimer’s disease pathology and cognitive decline. Sci Transl Med. 2021;13:612.

    Article  Google Scholar 

  48. Jones DT, Machulda MM, Vemuri P, McDade EM, Zeng G, Senjem ML, et al. Age-related changes in the default mode network are more advanced in Alzheimer disease. Neurology. 2011;77:1524–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Greicius MD, Srivastava G, Reiss AL, Menon V. Default-mode network activity distinguishes Alzheimer’s disease from healthy aging: Evidence from functional MRI. Proc Natl Acad Sci U S A. 2004;101:4637–42.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Rowland I, Gibson G, Heinken A, Scott K, Swann J, Thiele I, et al. Gut microbiota functions: metabolism of nutrients and other food components. Eur J Nutr. 2018;57:1–24.

    Article  CAS  PubMed  Google Scholar 

  51. Carabotti M, Scirocco A, Maselli MA, Severi C. The gut-brain axis: interactions between enteric microbiota, central and enteric nervous systems. Ann Gastroenterol. 2015;28:203–9.

    PubMed  PubMed Central  Google Scholar 

  52. Cryan JF, O’Riordan KJ, Cowan CSM, Sandhu KV, Bastiaanssen TFS, Boehme M, et al. The Microbiota-Gut-Brain Axis. Physiol Rev. 2019;99:1877–2013.

    Article  CAS  PubMed  Google Scholar 

  53. Foster JA, Rinaman L, Cryan JF. Stress & the gut-brain axis: Regulation by the microbiome. Neurobiology of Stress. 2017;7:124–36.

    Article  PubMed  PubMed Central  Google Scholar 

  54. Gareau MG, Wine E, Rodrigues DM, Cho JH, Whary MT, Philpott DJ, et al. Bacterial infection causes stress-induced memory dysfunction in mice. Gut BMJ Publishing Group. 2011;60:307–17.

    Google Scholar 

  55. Heijtz RD, Wang S, Anuar F, Qian Y, Björkholm B, Samuelsson A, et al. Normal gut microbiota modulates brain development and behavior. PNAS National Academy of Sciences. 2011;108:3047–52.

    Article  CAS  Google Scholar 

  56. Luczynski P, McVey Neufeld K-A, Oriach CS, Clarke G, Dinan TG, Cryan JF. Growing up in a Bubble: Using Germ-Free Animals to Assess the Influence of the Gut Microbiota on Brain and Behavior. Int J Neuropsychopharmacol. 2016;19:8.

    Article  CAS  Google Scholar 

  57. Bercik P, Denou E, Collins J, Jackson W, Lu J, Jury J, et al. The intestinal microbiota affect central levels of brain-derived neurotropic factor and behavior in mice. Gastroenterology. 2011;141(599–609):609.e1-3.

    Google Scholar 

  58. Diaz Heijtz R, Wang S, Anuar F, Qian Y, Björkholm B, Samuelsson A, et al. Normal gut microbiota modulates brain development and behavior. Proc Natl Acad Sci U S A. 2011;108:3047–52.

    Article  PubMed  Google Scholar 

  59. Baj G, Carlino D, Gardossi L, Tongiorgi E. Toward a unified biological hypothesis for the BDNF Val66Met-associated memory deficits in humans: a model of impaired dendritic mRNA trafficking. Front Neurosci. 2013;7:188.

    Article  PubMed  PubMed Central  Google Scholar 

  60. Lu K, Abo RP, Schlieper KA, Graffam ME, Levine S, Wishnok JS, et al. Arsenic exposure perturbs the gut microbiome and its metabolic profile in mice: an integrated metagenomics and metabolomics analysis. Environ Health Perspect. 2014;122:284–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Neufeld KM, Kang N, Bienenstock J, Foster JA. Reduced anxiety-like behavior and central neurochemical change in germ-free mice. Neurogastroenterol Motil. 2011;23:255–64.

    Article  CAS  PubMed  Google Scholar 

  62. Clarke G, Grenham S, Scully P, Fitzgerald P, Moloney RD, Shanahan F, et al. The microbiome-gut-brain axis during early life regulates the hippocampal serotonergic system in a sex-dependent manner. Molecular Psychiatry Nature Publishing Group. 2013;18:666–73.

    Article  CAS  Google Scholar 

  63. Lukić I, Getselter D, Koren O, Elliott E. Role of Tryptophan in Microbiota-Induced Depressive-Like Behavior: Evidence From Tryptophan Depletion Study. Front Behav Neurosci. 2019;13:123.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  64. Lyte JM, Gheorghe CE, Goodson MS, Kelley-Loughnane N, Dinan TG, Cryan JF, et al. Gut-brain axis serotonergic responses to acute stress exposure are microbiome-dependent. Neurogastroenterol Motil. 2020;32: e13881.

    Article  CAS  PubMed  Google Scholar 

  65. Matsumoto M, Kibe R, Ooga T, Aiba Y, Sawaki E, Koga Y, et al. Cerebral low-molecular metabolites influenced by intestinal microbiota: a pilot study. Front Syst Neurosci. 2013;7:9.

    Article  PubMed  PubMed Central  Google Scholar 

  66. Desbonnet L, Clarke G, Traplin A, O’Sullivan O, Crispie F, Moloney RD, et al. Gut microbiota depletion from early adolescence in mice: Implications for brain and behaviour. Brain Behav Immun. 2015;48:165–73.

    Article  CAS  PubMed  Google Scholar 

  67. Fröhlich EE, Farzi A, Mayerhofer R, Reichmann F, Jačan A, Wagner B, et al. Cognitive impairment by antibiotic-induced gut dysbiosis: Analysis of gut microbiota-brain communication. Brain Behav Immun. 2016;56:140–55.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  68. Verdu EF, Bercik P, Huang XX, Lu J, Al-Mutawaly N, Sakai H, et al. The role of luminal factors in the recovery of gastric function and behavioral changes after chronic Helicobacter pylori infection. American Journal of Physiology-Gastrointestinal and Liver Physiology. American Physiological Society; 2008;295:4.

  69. Azpiroz F, Dubray C, Bernalier-Donadille A, Cardot J-M, Accarino A, Serra J, et al. Effects of scFOS on the composition of fecal microbiota and anxiety in patients with irritable bowel syndrome: a randomized, double blind, placebo controlled study. Neurogastroenterol Motil. 2017;29:e12911.

  70. Burokas A, Arboleya S, Moloney RD, Peterson VL, Murphy K, Clarke G, et al. Targeting the Microbiota-Gut-Brain Axis: Prebiotics Have Anxiolytic and Antidepressant-like Effects and Reverse the Impact of Chronic Stress in Mice. Biol Psychiatry. 2017;82:472–87.

    Article  CAS  PubMed  Google Scholar 

  71. Liu X, Cao S, Zhang X. Modulation of Gut Microbiota–Brain Axis by Probiotics, Prebiotics, and Diet. J Agric Food Chem. American Chemical Society; 2015;63:7885–95.

  72. Marx W, Scholey A, Firth J, D’Cunha NM, Lane M, Hockey M, et al. Prebiotics, probiotics, fermented foods and cognitive outcomes: A meta-analysis of randomized controlled trials. Neurosci Biobehav Rev. 2020;118:472–84.

    Article  CAS  PubMed  Google Scholar 

  73. Pinto-Sanchez MI, Hall GB, Ghajar K, Nardelli A, Bolino C, Lau JT, et al. Probiotic Bifidobacterium longum NCC3001 Reduces Depression Scores and Alters Brain Activity: A Pilot Study in Patients With Irritable Bowel Syndrome. Gastroenterology Elsevier. 2017;153:448–59.

    Article  Google Scholar 

  74. Farhangi MA, Javid AZ, Sarmadi B, Karimi P, Dehghan P. A randomized controlled trial on the efficacy of resistant dextrin, as functional food, in women with type 2 diabetes: Targeting the hypothalamic-pituitary-adrenal axis and immune system. Clin Nutr. 2018;37:1216–23.

    Article  CAS  PubMed  Google Scholar 

  75. Jia S, Lu Z, Gao Z, An J, Wu X, Li X, et al. Chitosan oligosaccharides alleviate cognitive deficits in an amyloid-β1-42-induced rat model of Alzheimer’s disease. Int J Biol Macromol. 2016;83:416–25.

    Article  CAS  PubMed  Google Scholar 

  76. Odamaki T, Kato K, Sugahara H, Hashikura N, Takahashi S, Xiao J, et al. Age-related changes in gut microbiota composition from newborn to centenarian: a cross-sectional study. BMC Microbiol. 2016;16:90.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  77. O’Toole PW, Jeffery IB. Gut microbiota and aging. Science. 2015;350:1214–5.

    Article  PubMed  CAS  Google Scholar 

  78. Vogt NM, Kerby RL, Dill-McFarland KA, Harding SJ, Merluzzi AP, Johnson SC, et al. Gut microbiome alterations in Alzheimer’s disease. Scientific Reports Nature Publishing Group. 2017;7:13537.

    Article  CAS  Google Scholar 

  79. Sochocka M, Donskow-Łysoniewska K, Diniz BS, Kurpas D, Brzozowska E, Leszek J. The Gut Microbiome Alterations and Inflammation-Driven Pathogenesis of Alzheimer’s Disease—a Critical Review. Mol Neurobiol. 2019;56:1841–51.

    Article  CAS  PubMed  Google Scholar 

  80. Zhuang Z-Q, Shen L-L, Li W-W, Fu X, Zeng F, Gui L, et al. Gut Microbiota is Altered in Patients with Alzheimer’s Disease. Journal of Alzheimer’s Disease IOS Press. 2018;63:1337–46.

    Article  CAS  Google Scholar 

  81. Cattaneo A, Cattane N, Galluzzi S, Provasi S, Lopizzo N, Festari C, et al. Association of brain amyloidosis with pro-inflammatory gut bacterial taxa and peripheral inflammation markers in cognitively impaired elderly. Neurobiol Aging. 2017;49:60–8.

    Article  CAS  PubMed  Google Scholar 

  82. Haran JP, Bhattarai SK, Foley SE, Dutta P, Ward DV, Bucci V, et al. Alzheimer’s Disease Microbiome Is Associated with Dysregulation of the Anti-Inflammatory P-Glycoprotein Pathway. mBio. 2019;10:3.

  83. Verheggen ICM, de Jong JJA, van Boxtel MPJ, Gronenschild EHBM, Palm WM, Postma AA, et al. Increase in blood–brain barrier leakage in healthy, older adults. GeroScience. 2020;42:1183–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  84. Sweeney MD, Sagare AP, Zlokovic BV. Blood–brain barrier breakdown in Alzheimer’s disease and other neurodegenerative disorders. Nat Rev Neurol. 2018;14:133–50.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  85. Wu M-L, Yang X-Q, Xue L, Duan W, Du J-R. Age-related cognitive decline is associated with microbiota-gut-brain axis disorders and neuroinflammation in mice. Behav Brain Res. 2021;402: 113125.

    Article  CAS  PubMed  Google Scholar 

  86. Ticinesi A, Tana C, Nouvenne A, Prati B, Lauretani F, Meschi T. Gut microbiota, cognitive frailty and dementia in older individuals: a systematic review. Clin Interv Aging. 2018;13:1497–511.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Agostoni E, Chinnock JE, Daly MDB, Murray JG. Functional and histological studies of the vagus nerve and its branches to the heart, lungs and abdominal viscera in the cat. J Physiol. 1957;135:182–205.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Abreu MT, Fukata M, Arditi M. TLR Signaling in the Gut in Health and Disease. The Journal of Immunology. American Association of Immunologists; 2005;174:4453–60.

  89. Samuel BS, Shaito A, Motoike T, Rey FE, Backhed F, Manchester JK, et al. Effects of the gut microbiota on host adiposity are modulated by the short-chain fatty-acid binding G protein-coupled receptor, Gpr41. Proceedings of the National Academy of Sciences. Proceedings of the National Academy of Sciences; 2008;105:16767–72.

  90. Li Y, Hao Y, Zhu J, Owyang C. Serotonin released from intestinal enterochromaffin cells mediates luminal non–cholecystokinin-stimulated pancreatic secretion in rats. Gastroenterology. 2000;118:1197–207.

    Article  CAS  PubMed  Google Scholar 

  91. Strader AD, Woods SC. Gastrointestinal hormones and food intake. Gastroenterology. 2005;128:175–91.

    Article  CAS  PubMed  Google Scholar 

  92. Bravo JA, Forsythe P, Chew MV, Escaravage E, Savignac HM, Dinan TG, et al. Ingestion of Lactobacillus strain regulates emotional behavior and central GABA receptor expression in a mouse via the vagus nerve. Proceedings of the National Academy of Sciences. Proceedings of the National Academy of Sciences; 2011;108:16050–5.

  93. Bercik P, Park AJ, Sinclair D, Khoshdel A, Lu J, Huang X, et al. The anxiolytic effect of Bifidobacterium longum NCC3001 involves vagal pathways for gut–brain communication. Neurogastroenterol Motil. 2011;23:1132–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  94. Bercik P, Denou E, Collins J, Jackson W, Lu J, Jury J, et al. The Intestinal Microbiota Affect Central Levels of Brain-Derived Neurotropic Factor and Behavior in Mice. Gastroenterology. 2011;141:599–609.

    Article  CAS  PubMed  Google Scholar 

  95. Bajaj JS, Ridlon JM, Hylemon PB, Thacker LR, Heuman DM, Smith S, et al. Linkage of gut microbiome with cognition in hepatic encephalopathy. American Journal of Physiology-Gastrointestinal and Liver Physiology. American Physiological Society. 2012;302:168–75.

  96. Bajaj JS, Hylemon PB, Ridlon JM, Heuman DM, Daita K, White MB, et al. Colonic mucosal microbiome differs from stool microbiome in cirrhosis and hepatic encephalopathy and is linked to cognition and inflammation. American Journal of Physiology-Gastrointestinal and Liver Physiology. American Physiological Society. 2012;303:675–85.

  97. Racanelli V, Rehermann B. The liver as an immunological organ. Hepatology. 2006;43:54–62.

    Article  CAS  Google Scholar 

  98. Binder HJ, Filburn B, Floch M. Bile acid inhibition of intestinal anaerobic organisms. Am J Clin Nutr. 1975;28:119–25.

    Article  CAS  PubMed  Google Scholar 

  99. Hofmann AF, Eckmann L. How bile acids confer gut mucosal protection against bacteria. Proc Natl Acad Sci U S A. 2006;103:4333–4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  100. Inagaki T, Moschetta A, Lee Y-K, Peng L, Zhao G, Downes M, et al. Regulation of antibacterial defense in the small intestine by the nuclear bile acid receptor. Proc Natl Acad Sci U S A. 2006;103:3920–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Fukui H. Role of Gut Dysbiosis in Liver Diseases: What Have We Learned So Far? Diseases. 2019;7:58.

    Article  CAS  PubMed Central  Google Scholar 

  102. Bajaj JS, Heuman DM, Hylemon PB, Sanyal AJ, White MB, Monteith P, et al. Altered profile of human gut microbiome is associated with cirrhosis and its complications. J Hepatol. 2014;60:940–7.

    Article  CAS  PubMed  Google Scholar 

  103. Pande C, Kumar A, Sarin SK. Small-intestinal bacterial overgrowth in cirrhosis is related to the severity of liver disease. Aliment Pharmacol Ther. 2009;29:1273–81.

    Article  CAS  PubMed  Google Scholar 

  104. Kuang L, Zhou W, Jiang Y. Association of small intestinal bacterial overgrowth with nonalcoholic fatty liver disease in children: A meta-analysis. PLOS ONE. Public Library of Science. 2021;16:e0260479.

  105. Ding J-H, Jin Z, Yang X-X, Lou J, Shan W-X, Hu Y-X, et al. Role of gut microbiota via the gut-liver-brain axis in digestive diseases. World J Gastroenterol. 2020;26:6141–62.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Chiang JYL. Bile Acid Metabolism and Signaling. Compr Physiol. 2013;3:1191–212.

    Article  PubMed  PubMed Central  Google Scholar 

  107. Šarenac TM, Mikov M. Bile Acid Synthesis: From Nature to the Chemical Modification and Synthesis and Their Applications as Drugs and Nutrients. Front Pharmacol. 2018;9:939.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  108. Spichak S, Bastiaanssen TFS, Berding K, Vlckova K, Clarke G, Dinan TG, et al. Mining microbes for mental health: Determining the role of microbial metabolic pathways in human brain health and disease. Neurosci Biobehav Rev. 2021;125:698–761.

    Article  CAS  PubMed  Google Scholar 

  109. Guzior DV, Quinn RA. Review: microbial transformations of human bile acids. Microbiome. 2021;9:140.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Baloni P, Funk CC, Yan J, Yurkovich JT, Kueider-Paisley A, Nho K, et al. Metabolic Network Analysis Reveals Altered Bile Acid Synthesis and Metabolism in Alzheimer’s Disease. Cell Rep Med. 2020;1: 100138.

    Article  PubMed  PubMed Central  Google Scholar 

  111. McMillin M, DeMorrow S. Effects of bile acids on neurological function and disease. FASEB J. 2016;30:3658–68.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Kotti TJ, Ramirez DMO, Pfeiffer BE, Huber KM, Russell DW. Brain cholesterol turnover required for geranylgeraniol production and learning in mice. Proc Natl Acad Sci U S A. 2006;103:3869–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Higashi T, Watanabe S, Tomaru K, Yamazaki W, Yoshizawa K, Ogawa S, et al. Unconjugated bile acids in rat brain: Analytical method based on LC/ESI-MS/MS with chemical derivatization and estimation of their origin by comparison to serum levels. Steroids. 2017;125:107–13.

    Article  CAS  PubMed  Google Scholar 

  114. Mano N, Goto T, Uchida M, Nishimura K, Ando M, Kobayashi N, et al. Presence of protein-bound unconjugated bile acids in the cytoplasmic fraction of rat brain. J Lipid Res. 2004;45:295–300.

    Article  CAS  PubMed  Google Scholar 

  115. Pan X, Elliott CT, McGuinness B, Passmore P, Kehoe PG, Hölscher C, et al. Metabolomic Profiling of Bile Acids in Clinical and Experimental Samples of Alzheimer’s Disease. Metabolites. 2017;7:28.

  116. Quinn M, McMillin M, Galindo C, Frampton G, Pae HY, DeMorrow S. Bile acids permeabilize the blood brain barrier after bile duct ligation in rats via Rac1-dependent mechanisms. Dig Liver Dis. 2014;46:527–34.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  117. Kamp F, Hamilton JA, Kamp F, Westerhoff HV, Hamilton JA. Movement of fatty acids, fatty acid analogues, and bile acids across phospholipid bilayers. Biochemistry. 1993;32:11074–86.

    Article  CAS  PubMed  Google Scholar 

  118. Benedetti A, Di Sario A, Marucci L, Svegliati-Baroni G, Schteingart CD, Ton-Nu HT, et al. Carrier-mediated transport of conjugated bile acids across the basolateral membrane of biliary epithelial cells. Am J Physiol. 1997;272:1416–24.

    Google Scholar 

  119. Bron B, Waldram R, Silk DB, Williams R. Serum, cerebrospinal fluid, and brain levels of bile acids in patients with fulminant hepatic failure. Gut. 1977;18:692–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Cheng X, Maher J, Chen C, Klaassen CD. Tissue Distribution and Ontogeny of Mouse Organic Anion Transporting Polypeptides (oatps). Drug Metab Dispos. American Society for Pharmacology and Experimental Therapeutics. 2005;33:1062–73.

  121. Nizamutdinov D, DeMorrow S, McMillin M, Kain J, Mukherjee S, Zeitouni S, et al. Hepatic alterations are accompanied by changes to bile acid transporter-expressing neurons in the hypothalamus after traumatic brain injury. Scientific Reports. Nature Publishing Group. 2017;7:40112.

  122. Soontornmalai A, Vlaming MLH, Fritschy J-M. Differential, strain-specific cellular and subcellular distribution of multidrug transporters in murine choroid plexus and blood–brain barrier. Neuroscience. 2006;138:159–69.

    Article  CAS  PubMed  Google Scholar 

  123. Roberts LM, Black DS, Raman C, Woodford K, Zhou M, Haggerty JE, et al. Subcellular localization of transporters along the rat blood–brain barrier and blood–cerebral-spinal fluid barrier by in vivo biotinylation. Neuroscience. 2008;155:423–38.

    Article  CAS  PubMed  Google Scholar 

  124. Abbott NJ, Patabendige AAK, Dolman DEM, Yusof SR, Begley DJ. Structure and function of the blood–brain barrier. Neurobiol Dis. 2010;37:13–25.

    Article  CAS  PubMed  Google Scholar 

  125. Mertens KL, Kalsbeek A, Soeters MR, Eggink HM. Bile Acid Signaling Pathways from the Enterohepatic Circulation to the Central Nervous System. Front Neurosci. 2017;11:617.

  126. MahmoudianDehkordi S, Arnold M, Nho K, Ahmad S, Jia W, Xie G, et al. Altered bile acid profile associates with cognitive impairment in Alzheimer’s disease-An emerging role for gut microbiome. Alzheimer’s & Dementia: The Journal of the Alzheimer’s Association. 2019;15:76–92.

    Article  Google Scholar 

  127. Olazarán J, Gil-de-Gómez L, Rodríguez-Martín A, Valentí-Soler M, Frades-Payo B, Marín-Muñoz J, et al. A blood-based, 7-metabolite signature for the early diagnosis of Alzheimer’s disease. J Alzheimers Dis. 2015;45:1157–73.

    Article  PubMed  CAS  Google Scholar 

  128. Ignacio Barrasa J, Olmo N, Pérez-Ramos P, Santiago-Gómez A, Lecona E, Turnay J, et al. Deoxycholic and chenodeoxycholic bile acids induce apoptosis via oxidative stress in human colon adenocarcinoma cells. Apoptosis. 2011;16:1054–67.

    Article  PubMed  CAS  Google Scholar 

  129. Tran CD, Grice DM, Wade B, Kerr CA, Bauer DC, Li D, et al. Gut permeability, its interaction with gut microflora and effects on metabolic health are mediated by the lymphatics system, liver and bile acid. Future Microbiol. 2015;10:1339–53.

    Article  CAS  PubMed  Google Scholar 

  130. Jena PK, Sheng L, Di Lucente J, Jin L-W, Maezawa I, Wan Y-JY. Dysregulated bile acid synthesis and dysbiosis are implicated in Western diet-induced systemic inflammation, microglial activation, and reduced neuroplasticity. FASEB J. 2018;32:2866–77.

  131. Bernstein H, Bernstein C, Payne CM, Dvorak K. Bile acids as endogenous etiologic agents in gastrointestinal cancer. World J Gastroenterol. 2009;15:3329–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Dröge W, Schipper HM. Oxidative stress and aberrant signaling in aging and cognitive decline. Aging Cell. 2007;6:361–70.

    Article  PubMed  CAS  Google Scholar 

  133. Moreira PI, Carvalho C, Zhu X, Smith MA, Perry G. Mitochondrial dysfunction is a trigger of Alzheimer’s disease pathophysiology. Biochim Biophys Acta. 2010;1802:2–10.

    Article  CAS  PubMed  Google Scholar 

  134. Leloup C, Magnan C, Benani A, Bonnet E, Alquier T, Offer G, et al. Mitochondrial reactive oxygen species are required for hypothalamic glucose sensing. Diabetes. 2006;55:2084–90.

    Article  CAS  PubMed  Google Scholar 

  135. Theofilopoulos S, Wang Y, Kitambi SS, Sacchetti P, Sousa KM, Bodin K, et al. Brain endogenous liver X receptor ligands selectively promote midbrain neurogenesis. Nat Chem Biol Nature Publishing Group. 2013;9:126–33.

    Article  CAS  Google Scholar 

  136. Ramalho RM, Ribeiro PS, Solá S, Castro RE, Steer CJ, Rodrigues CMP. Inhibition of the E2F–1/p53/Bax pathway by tauroursodeoxycholic acid in amyloid beta-peptide-induced apoptosis of PC12 cells. J Neurochem. 2004;90:567–75.

    Article  CAS  PubMed  Google Scholar 

  137. Rodrigues CMP, Spellman SR, Solá S, Grande AW, Linehan-Stieers C, Low WC, et al. Neuroprotection by a Bile Acid in an Acute Stroke Model in the Rat. J Cereb Blood Flow Metab. SAGE Publications Ltd STM. 2002;22:463–71.

  138. Solá S, Amaral JD, Borralho PM, Ramalho RM, Castro RE, Aranha MM, et al. Functional modulation of nuclear steroid receptors by tauroursodeoxycholic acid reduces amyloid beta-peptide-induced apoptosis. Mol Endocrinol. 2006;20:2292–303.

    Article  PubMed  CAS  Google Scholar 

  139. Nunes AF, Amaral JD, Lo AC, Fonseca MB, Viana RJS, Callaerts-Vegh Z, et al. TUDCA, a bile acid, attenuates amyloid precursor protein processing and amyloid-β deposition in APP/PS1 mice. Mol Neurobiol. 2012;45:440–54.

    Article  CAS  PubMed  Google Scholar 

  140. Dionísio PA, Amaral JD, Ribeiro MF, Lo AC, D’Hooge R, Rodrigues CMP. Amyloid-β pathology is attenuated by tauroursodeoxycholic acid treatment in APP/PS1 mice after disease onset. Neurobiol Aging. 2015;36:228–40.

    Article  PubMed  CAS  Google Scholar 

  141. Yanguas-Casás N, Barreda-Manso MA, Nieto-Sampedro M, Romero-Ramírez L. TUDCA: An Agonist of the Bile Acid Receptor GPBAR1/TGR5 With Anti-Inflammatory Effects in Microglial Cells. J Cell Physiol. 2017;232:2231–45.

    Article  PubMed  CAS  Google Scholar 

  142. Soares R, Ribeiro FF, Xapelli S, Genebra T, Ribeiro MF, Sebastião AM, et al. Tauroursodeoxycholic Acid Enhances Mitochondrial Biogenesis, Neural Stem Cell Pool, and Early Neurogenesis in Adult Rats. Mol Neurobiol. 2018;55:3725–38.

    CAS  PubMed  Google Scholar 

  143. Cosacak MI, Bhattarai P, Kizil C. Alzheimer’s disease, neural stem cells and neurogenesis: cellular phase at single-cell level. Neural Regen Res. 2019;15:824–7.

    PubMed Central  Google Scholar 

  144. Craciun S, Balskus EP. Microbial conversion of choline to trimethylamine requires a glycyl radical enzyme. Proc Natl Acad Sci. 2012;109:21307–12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Stremmel W, Schmidt KV, Schuhmann V, Kratzer F, Garbade SF, Langhans C-D, et al. Blood Trimethylamine-N-Oxide Originates from Microbiota Mediated Breakdown of Phosphatidylcholine and Absorption from Small Intestine. PLoS One. 2017;12:e0170742.

  146. Wang S-Z, Yu Y-J, Adeli K. Role of Gut Microbiota in Neuroendocrine Regulation of Carbohydrate and Lipid Metabolism via the Microbiota-Gut-Brain-Liver Axis. Microorganisms. 2020;8:527.

    Article  CAS  PubMed Central  Google Scholar 

  147. Vogt NM, Romano KA, Darst BF, Engelman CD, Johnson SC, Carlsson CM, et al. The gut microbiota-derived metabolite trimethylamine N-oxide is elevated in Alzheimer’s disease. Alzheimer’s Research & Therapy. 2018;10:124.

    Article  CAS  Google Scholar 

  148. Ufnal M, Zadlo A, Ostaszewski R. TMAO: A small molecule of great expectations. Nutrition. 2015;31:1317–23.

    Article  CAS  PubMed  Google Scholar 

  149. Org E, Blum Y, Kasela S, Mehrabian M, Kuusisto J, Kangas AJ, et al. Relationships between gut microbiota, plasma metabolites, and metabolic syndrome traits in the METSIM cohort. Genome Biol. 2017;18:70.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  150. Del Rio D, Zimetti F, Caffarra P, Tassotti M, Bernini F, Brighenti F, et al. The Gut Microbial Metabolite Trimethylamine-N-Oxide Is Present in Human Cerebrospinal Fluid. Nutrients. 2017;9:1053.

    Article  PubMed Central  CAS  Google Scholar 

  151. Vernetti L, Gough A, Baetz N, Blutt S, Broughman JR, Brown JA, et al. Functional Coupling of Human Microphysiology Systems: Intestine, Liver, Kidney Proximal Tubule, Blood-Brain Barrier and Skeletal Muscle. Scientific Reports. Nature Publishing Group. 2017;7:42296.

  152. Nho K, Kueider-Paisley A, MahmoudianDehkordi S, Arnold M, Risacher SL, Louie G, et al. Altered Bile Acid Profile in Mild Cognitive Impairment and Alzheimer’s Disease: Relationship to Neuroimaging and CSF Biomarkers. Alzheimers Dement. 2019;15:232–44.

    Article  PubMed  Google Scholar 

  153. Mapstone M, Cheema AK, Fiandaca MS, Zhong X, Mhyre TR, MacArthur LH, et al. Plasma phospholipids identify antecedent memory impairment in older adults. Nature Medicine Nature Publishing Group. 2014;20:415–8.

    CAS  Google Scholar 

  154. Marksteiner J, Blasko I, Kemmler G, Koal T, Humpel C. Bile acid quantification of 20 plasma metabolites identifies lithocholic acid as a putative biomarker in Alzheimer’s disease. Metabolomics. 2017;14:1.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  155. Mitchell SC, Zhang AQ, Smith RL. Chemical and Biological Liberation of Trimethylamine from Foods. J Food Compos Anal. 2002;15:277–82.

    Article  CAS  Google Scholar 

  156. Zhang J, Cashman JR. Quantitative analysis of FMO gene mRNA levels in human tissues. Drug Metab Dispos. 2006;34:19–26.

    Article  PubMed  CAS  Google Scholar 

  157. Tang WHW, Wang Z, Fan Y, Levison B, Hazen JE, Donahue LM, et al. Prognostic value of elevated levels of intestinal microbe-generated metabolite trimethylamine-N-oxide in patients with heart failure: refining the gut hypothesis. J Am Coll Cardiol. 2014;64:1908–14.

    Article  CAS  PubMed  Google Scholar 

  158. Gao X, Liu X, Xu J, Xue C, Xue Y, Wang Y. Dietary trimethylamine N-oxide exacerbates impaired glucose tolerance in mice fed a high fat diet. J Biosci Bioeng. 2014;118:476–81.

    Article  CAS  PubMed  Google Scholar 

  159. Missailidis C, Hällqvist J, Qureshi AR, Barany P, Heimbürger O, Lindholm B, et al. Serum Trimethylamine-N-Oxide Is Strongly Related to Renal Function and Predicts Outcome in Chronic Kidney Disease. PLOS ONE. Public Library of Science. 2016;11:e0141738.

  160. Barrea L, Annunziata G, Muscogiuri G, Di Somma C, Laudisio D, Maisto M, et al. Trimethylamine-N-oxide (TMAO) as Novel Potential Biomarker of Early Predictors of Metabolic Syndrome. Nutrients. Multidisciplinary Digital Publishing Institute. 2018;10:1971.

  161. Li D, Ke Y, Zhan R, Liu C, Zhao M, Zeng A, et al. Trimethylamine‐N‐oxide promotes brain aging and cognitive impairment in mice. Aging Cell. 2018;17:e12768.

  162. Gao Q, Wang Y, Wang X, Zhang X, Wang R-T. Decreased levels of circulating trimethylamine N-oxide alleviate cognitive and pathological deterioration in transgenic mice: a potential therapeutic approach for Alzheimer’s disease. Aging. 2019;11:8642–63.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  163. Govindarajulu M, Pinky PD, Steinke I, Bloemer J, Ramesh S, Kariharan T, et al. Gut Metabolite TMAO Induces Synaptic Plasticity Deficits by Promoting Endoplasmic Reticulum Stress. Front Mol Neurosci Frontiers. 2020;13:138.

    Article  CAS  Google Scholar 

  164. Brunt VE, LaRocca TJ, Bazzoni AE, Sapinsley ZJ, Miyamoto-Ditmon J, Gioscia-Ryan RA, et al. The gut microbiome–derived metabolite trimethylamine N-oxide modulates neuroinflammation and cognitive function with aging. GeroScience. 2020;43:377–94.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  165. He W, Luo Y, Liu J-P, Sun N, Guo D, Cui L-L, et al. Trimethylamine N-Oxide, a Gut Microbiota-Dependent Metabolite, is Associated with Frailty in Older Adults with Cardiovascular Disease. Clin Interv Aging. 2020;15:1809–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  166. Zhu C, Li G, Lv Z, Li J, Wang X, Kang J, et al. Association of plasma trimethylamine-N-oxide levels with post-stroke cognitive impairment: a 1-year longitudinal study. Neurol Sci. 2020;41:57–63.

    Article  PubMed  Google Scholar 

  167. Zhuang Z, Gao M, Yang R, Liu Z, Cao W, Huang T. Causal relationships between gut metabolites and Alzheimer’s disease: a bidirectional Mendelian randomization study. Neurobiol Aging. 2020;100:119.

    PubMed  Google Scholar 

  168. Zhu W, Gregory JC, Org E, Buffa JA, Gupta N, Wang Z, et al. Gut Microbial Metabolite TMAO Enhances Platelet Hyperreactivity and Thrombosis Risk. Cell. 2016;165:111–24.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  169. Koeth RA, Wang Z, Levison BS, Buffa JA, Org E, Sheehy BT, et al. Intestinal microbiota metabolism of L-carnitine, a nutrient in red meat, promotes atherosclerosis. Nat Med. 2013;19:576–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  170. Chen M-L, Zhu X-H, Ran L, Lang H-D, Yi L, Mi M-T. Trimethylamine-N-Oxide Induces Vascular Inflammation by Activating the NLRP3 Inflammasome Through the SIRT3-SOD2-mtROS Signaling Pathway. J Am Heart Assoc. 2017;6:e006347.

  171. Seldin MM, Meng Y, Qi H, Zhu W, Wang Z, Hazen SL, et al. Trimethylamine N-Oxide Promotes Vascular Inflammation Through Signaling of Mitogen-Activated Protein Kinase and Nuclear Factor-κB. J Am Heart Assoc. 2016;5:e002767.

  172. Farso M, Ménard C, Colby-Milley J, Quirion R. The immune marker CD68 correlates with cognitive impairment in normally aged rats. Neurobiol Aging. 2013;34:1971–6.

    Article  CAS  PubMed  Google Scholar 

  173. Ownby RL. Neuroinflammation and cognitive aging. Curr Psychiatry Rep. 2010;12:39–45.

    Article  PubMed  Google Scholar 

  174. Simen AA, Bordner KA, Martin MP, Moy LA, Barry LC. Cognitive dysfunction with aging and the role of inflammation. Ther Adv Chronic Dis. 2011;2:175–95.

    Article  PubMed  PubMed Central  Google Scholar 

  175. Zhao L, Zhang C, Cao G, Dong X, Li D, Jiang L. Higher Circulating Trimethylamine N-oxide Sensitizes Sevoflurane-Induced Cognitive Dysfunction in Aged Rats Probably by Downregulating Hippocampal Methionine Sulfoxide Reductase A. Neurochem Res. 2019;44:2506–16.

    Article  CAS  PubMed  Google Scholar 

  176. Wang Q-J, Shen Y-E, Wang X, Fu S, Zhang X, Zhang Y-N, et al. Concomitant memantine and Lactobacillus plantarum treatment attenuates cognitive impairments in APP/PS1 mice. Aging (Albany NY). 2020;12:628–49.

    Article  CAS  Google Scholar 

  177. Hoyles L, Pontifex MG, Rodriguez-Ramiro I, Anis-Alavi MA, Jelane KS, Snelling T, et al. Regulation of blood-brain barrier integrity by microbiome-associated methylamines and cognition by trimethylamine N-oxide. Microbiome. 2021;9:235.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  178. McArthur S, Carvalho A, Fonseca S, Snelling T, Nicholson J, Glen R, et al. Effects of gut-derived trimethylamines on the blood-brain barrier. 2018.

  179. Tseng H-C, Graves DJ. Natural Methylamine Osmolytes, Trimethylamine N-Oxide and Betaine, Increase Tau-Induced Polymerization of Microtubules. Biochem Biophys Res Commun. 1998;250:726–30.

    Article  CAS  PubMed  Google Scholar 

  180. Smith M, Crowther RA, Goedert M. The natural osmolyte trimethylamine N-oxide (TMAO) restores the ability of mutant tau to promote microtubule assembly. FEBS Lett. 2000;484:265–70.

    Article  CAS  PubMed  Google Scholar 

  181. Tseng HC, Lu Q, Henderson E, Graves DJ. Phosphorylated tau can promote tubulin assembly. Proc Natl Acad Sci U S A. 1999;96:9503–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  182. Bose S, Cho J. Targeting chaperones, heat shock factor-1, and unfolded protein response: Promising therapeutic approaches for neurodegenerative disorders. Ageing Res Rev. 2017;35:155–75.

    Article  CAS  PubMed  Google Scholar 

  183. Velasquez MT, Ramezani A, Manal A, Raj DS. Trimethylamine N-Oxide: The Good, the Bad and the Unknown. Toxins (Basel). 2016;8:326.

    Article  PubMed Central  CAS  Google Scholar 

  184. Wang Z, Levison BS, Hazen JE, Donahue L, Li X-M, Hazen SL. Measurement of trimethylamine-N-oxide by stable isotope dilution liquid chromatography tandem mass spectrometry. Anal Biochem. 2014;455:35–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  185. Janeiro MH, Ramírez MJ, Milagro FI, Martínez JA, Solas M. Implication of Trimethylamine N-Oxide (TMAO) in Disease: Potential Biomarker or New Therapeutic Target. Nutrients. 2018;10:10.

    Article  CAS  Google Scholar 

  186. Costabile G, Vetrani C, Bozzetto L, Giacco R, Bresciani L, Del Rio D, et al. Plasma TMAO increase after healthy diets: results from 2 randomized controlled trials with dietary fish, polyphenols, and whole-grain cereals. Am J Clin Nutr. 2021;114:1342–50.

    Article  PubMed  Google Scholar 

  187. DiNicolantonio JJ, McCarty M, OKeefe J. Association of moderately elevated trimethylamine N-oxide with cardiovascular risk: is TMAO serving as a marker for hepatic insulin resistance. Open Heart. Archives of Disease in childhood; 2019;6:e000890.

  188. Li S, Shao Y, Li K, HuangFu C, Wang W, Liu Z, et al. Vascular Cognitive Impairment and the Gut Microbiota. J Alzheimers Dis. 2018;63:1209–22.

    Article  PubMed  Google Scholar 

  189. Xu R, Wang Q. Towards understanding brain-gut-microbiome connections in Alzheimer’s disease. BMC Syst Biol. 2016;10:63.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  190. Agus A, Planchais J, Sokol H. Gut Microbiota Regulation of Tryptophan Metabolism in Health and Disease. Cell Host Microbe. 2018;23:716–24.

    Article  CAS  PubMed  Google Scholar 

  191. Clarke G, Villalobos-Manriquez F, Marin DC. Tryptophan Metabolism and the Microbiome-Gut-Brain Axis. In: Burnet PW, editors. The Oxford Handbook of the Microbiome-Gut-Brain Axis. 2020.

  192. Richard DM, Dawes MA, Mathias CW, Acheson A, Hill-Kapturczak N, Dougherty DM. L-Tryptophan: Basic Metabolic Functions, Behavioral Research and Therapeutic Indications. Int J Tryptophan Res. 2009;2:45–60.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  193. Gao J, Xu K, Liu H, Liu G, Bai M, Peng C, et al. Impact of the Gut Microbiota on Intestinal Immunity Mediated by Tryptophan Metabolism. Front Cell Infect Microbiol. 2018;8:13.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  194. Wikoff WR, Anfora AT, Liu J, Schultz PG, Lesley SA, Peters EC, et al. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. PNAS. 2009;106:3698–703.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  195. Roager HM, Licht TR. Microbial tryptophan catabolites in health and disease. Nat Commun. 2018;9:3294.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  196. Jenkins TA, Nguyen JCD, Polglaze KE, Bertrand PP. Influence of Tryptophan and Serotonin on Mood and Cognition with a Possible Role of the Gut-Brain Axis. Nutrients. 2016;8:56.

  197. Savitz J. The kynurenine pathway: a finger in every pie. Mol Psychiatry. 2020;25:131–47.

    Article  PubMed  Google Scholar 

  198. Stone TW, Darlington LG. The kynurenine pathway as a therapeutic target in cognitive and neurodegenerative disorders. Br J Pharmacol. 2013;169:1211–27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  199. Dehhaghi M, Kazemi Shariat Panahi H, Guillemin GJ. Microorganisms, Tryptophan Metabolism, and Kynurenine Pathway: A Complex Interconnected Loop Influencing Human Health Status. Int J Tryptophan Res. 2019;12:1178646919852996.

  200. Agus A, Clément K, Sokol H. Gut microbiota-derived metabolites as central regulators in metabolic disorders. Gut BMJ Publishing Group. 2021;70:1174–82.

    CAS  Google Scholar 

  201. Badawy AA-B. Kynurenine Pathway of Tryptophan Metabolism: Regulatory and Functional Aspects. Int J Tryptophan Res. 2017;10:1178646917691938.

  202. Schwarcz R, Bruno JP, Muchowski PJ, Wu H-Q. Kynurenines in the mammalian brain: when physiology meets pathology. Nat Rev Neurosci. 2012;13:465–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  203. Lugo-Huitrón R, Ugalde Muñiz P, Pineda B, Pedraza-Chaverrí J, Ríos C, Pérez-de la Cruz V. Quinolinic Acid: An Endogenous Neurotoxin with Multiple Targets. Oxid Med Cell Longev. 2013;2013:104024.

  204. Ting KK, Brew BJ, Guillemin GJ. Effect of quinolinic acid on human astrocytes morphology and functions: implications in Alzheimer’s disease. J Neuroinflammation. 2009;6:36.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  205. Fujigaki H, Yamamoto Y, Saito K. L-Tryptophan-kynurenine pathway enzymes are therapeutic target for neuropsychiatric diseases: Focus on cell type differences. Neuropharmacology. 2017;112:264–74.

    Article  CAS  PubMed  Google Scholar 

  206. Hwu P, Du MX, Lapointe R, Do M, Taylor MW, Young HA. Indoleamine 2,3-dioxygenase production by human dendritic cells results in the inhibition of T cell proliferation. J Immunol. 2000;164:3596–9.

    Article  CAS  PubMed  Google Scholar 

  207. Gulaj E, Pawlak K, Bien B, Pawlak D. Kynurenine and its metabolites in Alzheimer’s disease patients. Adv Med Sci. 2010;55:204–11.

    Article  CAS  PubMed  Google Scholar 

  208. Yu D, Tao B-B, Yang Y-Y, Du L-S, Yang S-S, He X-J, et al. The IDO Inhibitor Coptisine Ameliorates Cognitive Impairment in a Mouse Model of Alzheimer’s Disease. Journal of Alzheimer’s Disease IOS Press. 2015;43:291–302.

    Article  CAS  Google Scholar 

  209. Ramos-Chávez LA, Roldán-Roldán G, García-Juárez B, González-Esquivel D, Pérez de la Cruz G, Pineda B, et al. Low Serum Tryptophan Levels as an Indicator of Global Cognitive Performance in Nondemented Women over 50 Years of Age. Oxid Med Cell Longev. 2018;2018:2018:8604718.

  210. Smith JA, Das A, Ray SK, Banik NL. Role of pro-inflammatory cytokines released from microglia in neurodegenerative diseases. Brain Res Bull. 2012;87:10–20.

    Article  CAS  PubMed  Google Scholar 

  211. Yamada A, Akimoto H, Kagawa S, Guillemin GJ, Takikawa O. Proinflammatory cytokine interferon-γ increases induction of indoleamine 2,3-dioxygenase in monocytic cells primed with amyloid β peptide 1–42: implications for the pathogenesis of Alzheimer’s disease. J Neurochem. 2009;110:791–800.

    Article  CAS  PubMed  Google Scholar 

  212. Liebau C, Baltzer AWA, Schmidt S, Roesel C, Karreman C, Prisack JB, et al. Interleukin-12 and interleukin-18 induce indoleamine 2,3-dioxygenase (IDO) activity in human osteosarcoma cell lines independently from interferon-gamma. Anticancer Res. 2002;22:931–6.

    CAS  PubMed  Google Scholar 

  213. Solvang S-EH, Nordrehaug JE, Tell GS, Nygård O, McCann A, Ueland PM, et al. The kynurenine pathway and cognitive performance in community-dwelling older adults. The Hordaland Health Study. Brain Behav Immun. 2019;75:155–62.

  214. Mithaiwala MN, Santana-Coelho D, Porter GA, O’Connor JC. Neuroinflammation and the Kynurenine Pathway in CNS Disease: Molecular Mechanisms and Therapeutic Implications. Cells. 2021;10:1548.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  215. Guillemin GJ, Brew BJ, Noonan CE, Takikawa O, Cullen KM. Indoleamine 2,3 dioxygenase and quinolinic acid immunoreactivity in Alzheimer’s disease hippocampus. Neuropathol Appl Neurobiol. 2005;31:395–404.

    Article  CAS  PubMed  Google Scholar 

  216. Heyes MP, Morrison PF. Quantification of local de novo synthesis versus blood contributions to quinolinic acid concentrations in brain and systemic tissues. J Neurochem. 1997;68:280–8.

    Article  CAS  PubMed  Google Scholar 

  217. Rahman A, Ting K, Cullen KM, Braidy N, Brew BJ, Guillemin GJ. The Excitotoxin Quinolinic Acid Induces Tau Phosphorylation in Human Neurons. PLOS ONE. Public Library of Science; 2009;4:e6344.

  218. Zwilling D, Huang S-Y, Sathyasaikumar KV, Notarangelo FM, Guidetti P, Wu H-Q, et al. Kynurenine 3-monooxygenase inhibition in blood ameliorates neurodegeneration. Cell. 2011;145:863–74.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  219. Crockett MJ, Clark L, Roiser JP, Robinson OJ, Cools R, Chase HW, et al. Converging evidence for central 5-HT effects in acute tryptophan depletion. Mol Psychiatry. 2012;17:121–3.

    Article  CAS  PubMed  Google Scholar 

  220. Hughes MM, Carballedo A, McLoughlin DM, Amico F, Harkin A, Frodl T, et al. Tryptophan depletion in depressed patients occurs independent of kynurenine pathway activation. Brain Behav Immun. 2012;26:979–87.

    Article  CAS  PubMed  Google Scholar 

  221. van Donkelaar EL, Blokland A, Ferrington L, Kelly P a. T, Steinbusch HWM, Prickaerts J. Mechanism of acute tryptophan depletion: is it only serotonin? Mol Psychiatry. 2011;16:695–713.

  222. El-Merahbi R, Löffler M, Mayer A, Sumara G. The roles of peripheral serotonin in metabolic homeostasis. FEBS Lett. 2015;589:1728–34.

    Article  CAS  PubMed  Google Scholar 

  223. Höglund E, Øverli Ø, Winberg S. Tryptophan Metabolic Pathways and Brain Serotonergic Activity: A Comparative Review. Front Endocrinol. 2019;10:158.

    Article  Google Scholar 

  224. Lovelace MD, Varney B, Sundaram G, Lennon MJ, Lim CK, Jacobs K, et al. Recent evidence for an expanded role of the kynurenine pathway of tryptophan metabolism in neurological diseases. Neuropharmacology. 2017;112:373–88.

    Article  CAS  PubMed  Google Scholar 

  225. Oxenkrug G. Serotonin-kynurenine hypothesis of depression: historical overview and recent developments. Curr Drug Targets. 2013;14:514–21.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  226. Cowen P, Sherwood A. The role of serotonin in cognitive function: Evidence from recent studies and implications for understanding depression. Journal of psychopharmacology (Oxford, England). 2013;27:575–83.

    Article  CAS  Google Scholar 

  227. Schmitt JAJ, Wingen M, Ramaekers JG, Evers EAT, Riedel WJ. Serotonin and Human Cognitive Performance. Curr Pharm Des. 2006;12:2473–86.

    Article  CAS  PubMed  Google Scholar 

  228. Cowen PJ, Browning M. What has serotonin to do with depression? World Psychiatry. 2015;14:158–60.

    Article  PubMed  PubMed Central  Google Scholar 

  229. Porter RJ, Lunn BS, Walker LLM, Gray JM, Ballard CG, O’Brien JT. Cognitive Deficit Induced by Acute Tryptophan Depletion in Patients With Alzheimer’s Disease. AJP American Psychiatric Publishing. 2000;157:638–40.

    Article  CAS  Google Scholar 

  230. Haider S, Khaliq S, Haleem DJ. Enhanced serotonergic neurotransmission in the hippocampus following tryptophan administration improves learning acquisition and memory consolidation in rats. Pharmacol Rep. 2007;59:53–7.

    CAS  PubMed  Google Scholar 

  231. Levkovitz Y, Richter-Levin G, Segal M. Effect of 5-hydroxytryptophane on behavior and hippocampal physiology in young and old rats. Neurobiol Aging. 1994;15:635–41.

    Article  CAS  PubMed  Google Scholar 

  232. Kaddurah-Daouk R, Zhu H, Sharma S, Bogdanov M, Rozen SG, Matson W, et al. Alterations in metabolic pathways and networks in Alzheimer’s disease. Transl Psychiatry. 2013;3: e244.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  233. Zelante T, Iannitti RG, Cunha C, De Luca A, Giovannini G, Pieraccini G, et al. Tryptophan catabolites from microbiota engage aryl hydrocarbon receptor and balance mucosal reactivity via interleukin-22. Immunity. 2013;39:372–85.

    Article  CAS  PubMed  Google Scholar 

  234. Hubbard TD, Murray IA, Bisson WH, Lahoti TS, Gowda K, Amin SG, et al. Adaptation of the human aryl hydrocarbon receptor to sense microbiota-derived indoles. Sci Rep. 2015;5:12689.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  235. Cheng Y, Jin U-H, Allred CD, Jayaraman A, Chapkin RS, Safe S. Aryl Hydrocarbon Receptor Activity of Tryptophan Metabolites in Young Adult Mouse Colonocytes. Drug Metab Dispos. American Society for Pharmacology and Experimental Therapeutics; 2015;43:1536–43.

  236. Cervantes-Barragan L, Chai JN, Tianero MD, Di Luccia B, Ahern PP, Merriman J, et al. Lactobacillus reuteri induces gut intraepithelial CD4+CD8αα+ T cells. Science. 2017;357:806–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  237. Schroeder JC, DiNatale BC, Murray IA, Flaveny CA, Liu Q, Laurenzana EM, et al. The Uremic Toxin 3-Indoxyl Sulfate Is a Potent Endogenous Agonist for the Human Aryl Hydrocarbon Receptor. Biochemistry American Chemical Society. 2010;49:393–400.

    CAS  Google Scholar 

  238. Hubbard T, Murray I, Bisson W, Lahoti T, Gowda K, Amin S, et al. Adaptation of the human aryl hydrocarbon receptor to sense microbiota-derived indoles. Scientific Reports. 2015;5:12689.

  239. Ramos-García NA, Orozco-Ibarra M, Estudillo E, Elizondo G, Gómez Apo E, Chávez Macías LG, et al. Aryl Hydrocarbon Receptor in Post-Mortem Hippocampus and in Serum from Young, Elder, and Alzheimer’s Patients. International Journal of Molecular Sciences. Multidisciplinary Digital Publishing Institute; 2020;21:1983.

  240. Rothhammer V, Mascanfroni ID, Bunse L, Takenaka MC, Kenison JE, Mayo L, et al. Type I interferons and microbial metabolites of tryptophan modulate astrocyte activity and CNS inflammation via the aryl hydrocarbon receptor. Nat Med. 2016;22:586–97.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  241. Wei GZ, Martin KA, Xing PY, Agrawal R, Whiley L, Wood TK, et al. Tryptophan-metabolizing gut microbes regulate adult neurogenesis via the aryl hydrocarbon receptor. Proceedings of the National Academy of Sciences. Proceedings of the National Academy of Sciences; 2021;118:e2021091118.

  242. Bansal T, Alaniz RC, Wood TK, Jayaraman A. The bacterial signal indole increases epithelial-cell tight-junction resistance and attenuates indicators of inflammation. Proc Natl Acad Sci U S A. 2010;107:228–33.

    Article  CAS  PubMed  Google Scholar 

  243. Shimada Y, Kinoshita M, Harada K, Mizutani M, Masahata K, Kayama H, et al. Commensal bacteria-dependent indole production enhances epithelial barrier function in the colon. PLoS ONE. 2013;8: e80604.

    Article  PubMed  PubMed Central  Google Scholar 

  244. Yu M, Wang Q, Ma Y, Li L, Yu K, Zhang Z, et al. Aryl Hydrocarbon Receptor Activation Modulates Intestinal Epithelial Barrier Function by Maintaining Tight Junction Integrity. Int J Biol Sci. 2018;14:69–77.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  245. Wlodarska M, Luo C, Kolde R, d’Hennezel E, Annand JW, Heim CE, et al. Indoleacrylic Acid Produced by Commensal Peptostreptococcus Species Suppresses Inflammation. Cell Host Microbe. 2017;22:25-37.e6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  246. Joshi G, Johnson JA. The Nrf2-ARE pathway: a valuable therapeutic target for the treatment of neurodegenerative diseases. Recent Pat CNS Drug Discov. 2012;7:218–29.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  247. Tian Y, Wang W, Xu L, Li H, Wei Y, Wu Q, et al. Activation of Nrf2/ARE pathway alleviates the cognitive deficits in PS1V97L-Tg mouse model of Alzheimer’s disease through modulation of oxidative stress. J Neurosci Res. 2019;97:492–505.

    Article  CAS  PubMed  Google Scholar 

  248. Liu Y, Li N, Zhou L, Li Q, Li W. Plasma metabolic profiling of mild cognitive impairment and Alzheimer’s disease using liquid chromatography/mass spectrometry. Cent Nerv Syst Agents Med Chem. 2014;14:113–20.

    Article  CAS  PubMed  Google Scholar 

  249. Fülling C, Dinan TG, Cryan JF. Gut microbe to brain signaling: what happens in vagus. Neuron. 2019;101:998–1002.

    Article  PubMed  CAS  Google Scholar 

  250. Strandwitz P. Neurotransmitter modulation by the gut microbiota. Brain Res. 2018;1693:128–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  251. Hyland NP, Cryan JF. A gut feeling about GABA: focus on GABAB receptors. Front Pharmacol. 2010;1:124.

    Article  PubMed  PubMed Central  Google Scholar 

  252. Boonstra E, de Kleijn R, Colzato LS, Alkemade A, Forstmann BU, Nieuwenhuis S. Neurotransmitters as food supplements: the effects of GABA on brain and behavior. Front Psychol. 2015;6:1520.

    Article  PubMed  PubMed Central  Google Scholar 

  253. Matsumoto M, Kibe R, Ooga T, Aiba Y, Kurihara S, Sawaki E, et al. Impact of Intestinal Microbiota on Intestinal Luminal Metabolome. Sci Rep. Nature Publishing Group; 2012;2:233.

  254. Deng P, Valentino T, Flythe MD, Moseley HNB, Leachman JR, Morris AJ, et al. Untargeted stable isotope probing of the gut microbiota metabolome using 13C-labeled dietary fibers. J Proteome Res American Chemical Society. 2021;20:2904–13.

    Article  CAS  Google Scholar 

  255. Strandwitz P, Kim KH, Terekhova D, Liu JK, Sharma A, Levering J, et al. GABA-modulating bacteria of the human gut microbiota. Nat Microbiol Nature Publishing Group. 2019;4:396–403.

    Article  CAS  Google Scholar 

  256. Needham BD, Kaddurah-Daouk R, Mazmanian SK. Gut microbial molecules in behavioural and neurodegenerative conditions. Nat Rev Neurosci Nature Publishing Group. 2020;21:717–31.

    Article  CAS  Google Scholar 

  257. Janik R, Thomason LAM, Stanisz AM, Forsythe P, Bienenstock J, Stanisz GJ. Magnetic resonance spectroscopy reveals oral lactobacillus promotion of increases in brain GABA. N-acetyl aspartate and glutamate NeuroImage. 2016;125:988–95.

    CAS  PubMed  Google Scholar 

  258. Saito Y, Sato T, Nomoto K, Tsuji H. Identification of phenol- and p-cresol-producing intestinal bacteria by using media supplemented with tyrosine and its metabolites. FEMS Microbiol Ecol. 2018;94:9.

    Article  CAS  Google Scholar 

  259. Cerini C, Dou L, Anfosso F, Sabatier F, Moal V, Glorieux G, et al. P-cresol, a uremic retention solute, alters the endothelial barrier function in vitro. Thromb Haemost. 2004;92:140–50.

    Article  CAS  PubMed  Google Scholar 

  260. Pascucci T, Colamartino M, Fiori E, Sacco R, Coviello A, Ventura R, et al. P-cresol Alters Brain Dopamine Metabolism and Exacerbates Autism-Like Behaviors in the BTBR Mouse. Brain Sciences. Multidisciplinary Digital Publishing Institute; 2020;10:233.

  261. Sankowski B, Księżarczyk K, Raćkowska E, Szlufik S, Koziorowski D, Giebułtowicz J. Higher cerebrospinal fluid to plasma ratio of p-cresol sulfate and indoxyl sulfate in patients with Parkinson’s disease. Clin Chim Acta. 2020;501:165–73.

    Article  CAS  PubMed  Google Scholar 

  262. Al-Bachari S, Naish JH, Parker GJM, Emsley HCA, Parkes LM. Blood-brain barrier leakage is increased in parkinson’s disease. Front Physiol. 2020;11: 593026.

    Article  PubMed  PubMed Central  Google Scholar 

  263. Azevedo MLV, Bonan NB, Dias G, Brehm F, Steiner TM, Souza WM, et al. p-Cresyl sulfate affects the oxidative burst, phagocytosis process, and antigen presentation of monocyte-derived macrophages. Toxicol Lett. 2016;263:1–5.

    Article  CAS  PubMed  Google Scholar 

  264. Edamatsu T, Fujieda A, Itoh Y. Phenyl sulfate, indoxyl sulfate and p-cresyl sulfate decrease glutathione level to render cells vulnerable to oxidative stress in renal tubular cells. PLOS ONE. Public Library of Science; 2018;13:e0193342.

  265. Sun C-Y, Cheng M-L, Pan H-C, Lee J-H, Lee C-C. Protein-bound uremic toxins impaired mitochondrial dynamics and functions. Oncotarget Impact Journals. 2017;8:77722–33.

    Article  Google Scholar 

  266. Tang W-H, Wang C-P, Yu T-H, Tai P-Y, Liang S-S, Hung W-C, et al. Protein-bounded uremic toxin p-cresylsulfate induces vascular permeability alternations. Histochem Cell Biol. 2018;149:607–17.

    Article  CAS  PubMed  Google Scholar 

  267. Sun C-Y, Li J-R, Wang Y-Y, Lin S-Y, Ou Y-C, Lin C-J, et al. p-Cresol sulfate caused behavior disorders and neurodegeneration in mice with unilateral nephrectomy involving oxidative stress and neuroinflammation. Int J Mol Sci. 2020;21:E6687.

    Article  PubMed  CAS  Google Scholar 

  268. Koh A, Molinaro A, Ståhlman M, Khan MT, Schmidt C, Mannerås-Holm L, et al. Microbially produced imidazole propionate impairs insulin signaling through mTORC1. Cell. 2018;175:947-961.e17.

    Article  CAS  PubMed  Google Scholar 

  269. Molinaro A, Bel Lassen P, Henricsson M, Wu H, Adriouch S, Belda E, et al. Imidazole propionate is increased in diabetes and associated with dietary patterns and altered microbial ecology. Nat Commun. 2020;11:5881.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  270. Le Chatelier E, Nielsen T, Qin J, Prifti E, Hildebrand F, Falony G, et al. Richness of human gut microbiome correlates with metabolic markers. Nature. 2013;500:541–6.

    Article  PubMed  CAS  Google Scholar 

  271. Koh A, Mannerås-Holm L, Yunn N-O, Nilsson PM, Ryu SH, Molinaro A, et al. Microbial imidazole propionate affects responses to metformin through p38γ-dependent inhibitory AMPK phosphorylation. Cell Metab. 2020;32:643-653.e4.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  272. Ott A, Stolk RP, van Harskamp F, Pols HA, Hofman A, Breteler MM. Diabetes mellitus and the risk of dementia: the rotterdam study. Neurology. 1999;53:1937–42.

    Article  CAS  PubMed  Google Scholar 

  273. Peila R, Rodriguez BL, Launer LJ. Type 2 diabetes, APOE gene, and the risk for dementia and related pathologies: the honolulu-asia aging study. Diabetes American Diabetes Association. 2002;51:1256–62.

    CAS  Google Scholar 

  274. Nicholson JK, Holmes E, Kinross J, Burcelin R, Gibson G, Jia W, et al. Host-gut microbiota metabolic interactions. Science. 2012;336:1262–7.

    Article  CAS  PubMed  Google Scholar 

  275. Luan H, Wang X, Cai Z. Mass spectrometry-based metabolomics: targeting the crosstalk between gut microbiota and brain in neurodegenerative disorders. Mass Spectrom Rev. 2019;38:22–33.

    Article  CAS  PubMed  Google Scholar 

  276. Smith EA, Macfarlane GT. Dissimilatory amino acid metabolism in human colonic bacteria. Anaerobe. 1997;3:327–37.

    Article  CAS  PubMed  Google Scholar 

  277. Ferreira-Vieira TH, Guimaraes IM, Silva FR, Ribeiro FM. Alzheimer’s disease: targeting the cholinergic system. Curr Neuropharmacol. 2016;14:101–15.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  278. Fricker RA, Green EL, Jenkins SI, Griffin SM. The Influence of Nicotinamide on Health and Disease in the Central Nervous System. Int J Tryptophan Res. 2018;11:1178646918776658.

  279. Phelan M, Phase II. Clinical Trial of Nicotinamide for the Treatment of Mild to Moderate Alzheimer’s Disease. Journal of Geriatric Medicine and Gerontology. 2017;3:1–7.

    Article  Google Scholar 

  280. Kim L-J, Chalmers TJ, Smith GC, Das A, Poon EWK, Wang J, et al. Nicotinamide mononucleotide (NMN) deamidation by the gut microbiome and evidence for indirect upregulation of the NAD+ metabolome. bioRxiv. Cold Spring Harbor Laboratory; 2020;289561:1–85.

  281. Wang D, Ho L, Faith J, Ono K, Janle EM, Lachcik PJ, et al. Role of intestinal microbiota in the generation of polyphenol-derived phenolic acid mediated attenuation of Alzheimer’s disease β-amyloid oligomerization. Mol Nutr Food Res. 2015;59:1025–40.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  282. Faria A, Mateus N, Calhau C. Flavonoid transport across blood-brain barrier: implication for their direct neuroprotective actions. Nutrition and Aging IOS Press. 2012;1:89–97.

    Article  Google Scholar 

  283. Faundes V, Jennings MD, Crilly S, Legraie S, Withers SE, Cuvertino S, et al. Impaired eIF5A function causes a Mendelian disorder that is partially rescued in model systems by spermidine. Nat Commun. Nature Publishing Group; 2021;12:833.

  284. Guerra GP, Rubin MA, Mello CF. Modulation of learning and memory by natural polyamines. Pharmacol Res. 2016;112:99–118.

    Article  CAS  PubMed  Google Scholar 

  285. Leclerc M, Dudonné S, Calon F. Can Natural Products Exert Neuroprotection without Crossing the Blood-Brain Barrier? Int J Mol Sci. 2021;22:3356.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  286. Szwajgier D, Borowiec K, Pustelniak K. The Neuroprotective Effects of Phenolic Acids: Molecular Mechanism of Action. Nutrients. 2017;9:477.

    Article  PubMed Central  CAS  Google Scholar 

  287. Hankes LV, Coenen HH, Rota E, Langen KJ, Herzog H, Wutz W, et al. Effect of huntington’s and alzheimer’s diseases on the transport of nicotinic acid or nicotinamide across the human blood-brain barrier. Adv Exp Med Biol. 1991;294:675–8.

    Article  CAS  PubMed  Google Scholar 

  288. Hole KL, Williams RJ. Flavonoids as an intervention for alzheimer’s disease: progress and hurdles towards defining a mechanism of action. Brain Plasticity IOS Press. 2020;6:167–92.

    Article  Google Scholar 

  289. Carecho R, Carregosa D, dos Santos CN. Low molecular weight (poly)phenol metabolites across the blood-brain barrier: the underexplored journey. Brain Plasticity IOS Press. 2020;6:193–214.

    Article  Google Scholar 

  290. Ho L, Ono K, Tsuji M, Mazzola P, Singh R, Pasinetti GM. Protective roles of intestinal microbiota derived short chain fatty acids in Alzheimer’s disease-type beta-amyloid neuropathological mechanisms. Expert Review of Neurotherapeutics. Taylor & Francis; 2018;18:83–90.

  291. Berding K, Carbia C, Cryan JF. Going with the grain: Fiber, cognition, and the microbiota-gut-brain-axis. Exp Biol Med (Maywood). SAGE Publications; 2021;246:796–811.

  292. Vijay N, Morris ME. Role of Monocarboxylate Transporters in Drug Delivery to the Brain. Current Pharmaceutical Design. 2014;20:1487–98.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  293. Oldendorf W. Carrier-mediated blood-brain barrier transport of short-chain monocarboxylic organic acids. American Journal of Physiology-Legacy Content. American Physiological Society; 1973;224:1450–3.

  294. Braniste V, Al-Asmakh M, Kowal C, Anuar F, Abbaspour A, Tóth M, et al. The gut microbiota influences blood-brain barrier permeability in mice. Sci Transl Med. 2014;6:263ra158.

  295. Li H, Sun J, Wang F, Ding G, Chen W, Fang R, et al. Sodium butyrate exerts neuroprotective effects by restoring the blood-brain barrier in traumatic brain injury mice. Brain Res. 2016;1642:70–8.

    Article  CAS  PubMed  Google Scholar 

  296. Harman MF, Martín MG. Epigenetic mechanisms related to cognitive decline during aging. J Neurosci Res. 2020;98:234–46.

    Article  CAS  PubMed  Google Scholar 

  297. Patnala R, Arumugam TV, Gupta N, Dheen ST. HDAC Inhibitor sodium butyrate-mediated epigenetic regulation enhances neuroprotective function of microglia during ischemic stroke. Mol Neurobiol. 2017;54:6391–411.

    Article  CAS  PubMed  Google Scholar 

  298. Huuskonen J, Suuronen T, Nuutinen T, Kyrylenko S, Salminen A. Regulation of microglial inflammatory response by sodium butyrate and short-chain fatty acids. Br J Pharmacol. 2004;141:874–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  299. Wei YB, Melas PA, Wegener G, Mathé AA, Lavebratt C. Antidepressant-Like Effect of Sodium Butyrate is Associated with an Increase in TET1 and in 5-Hydroxymethylation Levels in the Bdnf Gene. International Journal of Neuropsychopharmacology. 2015;18:pyu032.

  300. Shin H, Kim J-H, Lee YS, Lee YC. Change in gene expression profiles of secreted frizzled-related proteins (SFRPs) by sodium butyrate in gastric cancers: Induction of promoter demethylation and histone modification causing inhibition of Wnt signaling. International Journal of Oncology Spandidos Publications. 2012;40:1533–42.

    CAS  Google Scholar 

  301. Sarkar S, Abujamra AL, Loew JE, Forman LW, Perrine SP, Faller DV. Histone Deacetylase Inhibitors Reverse CpG Methylation by Regulating DNMT1 through ERK Signaling. Anticancer Research. International Institute of Anticancer Research; 2011;31:2723–32.

  302. Yamawaki Y, Yoshioka N, Nozaki K, Ito H, Oda K, Harada K, et al. Sodium butyrate abolishes lipopolysaccharide-induced depression-like behaviors and hippocampal microglial activation in mice. Brain Res. 2018;1680:13–38.

    Article  CAS  PubMed  Google Scholar 

  303. Soliman ML, Smith MD, Houdek HM, Rosenberger TA. Acetate supplementation modulates brain histone acetylation and decreases interleukin-1β expression in a rat model of neuroinflammation. J Neuroinflammation. 2012;9:51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  304. Soliman ML, Combs CK, Rosenberger TA. Modulation of inflammatory cytokines and mitogen-activated protein kinases by acetate in primary astrocytes. J Neuroimmune Pharmacol. 2013;8:287–300.

    Article  PubMed  Google Scholar 

  305. Wang P, Zhang Y, Gong Y, Yang R, Chen Z, Hu W, et al. Sodium butyrate triggers a functional elongation of microglial process via Akt-small RhoGTPase activation and HDACs inhibition. Neurobiol Dis. 2018;111:12–25.

    Article  CAS  PubMed  Google Scholar 

  306. Den Besten G, Van Eunen K, Groen AK, Venema K, Reijngoud D-J, Bakker BM. The role of short-chain fatty acids in the interplay between diet, gut microbiota, and host energy metabolism. J Lipid Res. 2013;54:2325–40.

    Article  CAS  Google Scholar 

  307. Zilberter Y, Zilberter M. The vicious circle of hypometabolism in neurodegenerative diseases: ways and mechanisms of metabolic correction. J Neurosci Res. 2017;95:2217–35.

    Article  CAS  PubMed  Google Scholar 

  308. Reddy DS, Wu X, Golub VM, Dashwood WM, Dashwood RH. Measuring histone deacetylase inhibition in the brain. Curr Protoc Pharmacol. 2018;81: e41.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  309. Colombo AV, Sadler RK, Llovera G, Singh V, Roth S, Heindl S, et al. Microbiota-derived short chain fatty acids modulate microglia and promote Aβ plaque deposition. Elife. 2021;10: e59826.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  310. Marizzoni M, Cattaneo A, Mirabelli P, Festari C, Lopizzo N, Nicolosi V, et al. Short-chain fatty acids and lipopolysaccharide as mediators between gut dysbiosis and amyloid pathology in alzheimer’s disease. J Alzheimers Dis. 2020;78:683–97.

    Article  CAS  PubMed  Google Scholar 

  311. Tran TTT, Corsini S, Kellingray L, Hegarty C, Le Gall G, Narbad A, et al. APOE genotype influences the gut microbiome structure and function in humans and mice: relevance for alzheimer’s disease pathophysiology. Faseb J. 2019;33:8221–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  312. Nguyen TTT, Fujimura Y, Mimura I, Fujii Y, Nguyen NL, Arakawa K, et al. Cultivable butyrate-producing bacteria of elderly japanese diagnosed with alzheimer’s disease. J Microbiol. 2018;56:760–71.

    Article  CAS  PubMed  Google Scholar 

  313. Liebisch G, Ecker J, Roth S, Schweizer S, Öttl V, Schött H-F, et al. Quantification of Fecal Short Chain Fatty Acids by Liquid Chromatography Tandem Mass Spectrometry—Investigation of Pre-Analytic Stability. Biomolecules. Multidisciplinary Digital Publishing Institute; 2019;9:121.

  314. Hamer HM, Jonkers D, Venema K, Vanhoutvin S, Troost FJ, Brummer R-J. Review article: the role of butyrate on colonic function. Aliment Pharmacol Ther. 2008;27:104–19.

    Article  CAS  PubMed  Google Scholar 

  315. Stilling RM, van de Wouw M, Clarke G, Stanton C, Dinan TG, Cryan JF. The neuropharmacology of butyrate: The bread and butter of the microbiota-gut-brain axis? Neurochem Int. 2016;99:110–32.

    Article  CAS  PubMed  Google Scholar 

  316. Horiuchi Y, Kimura R, Kato N, Fujii T, Seki M, Endo T, et al. Evolutional study on acetylcholine expression. Life Sci. 2003;72:1745–56.

    Article  CAS  PubMed  Google Scholar 

  317. Koussoulas K, Swaminathan M, Fung C, Bornstein JC, Foong JPP. Neurally released GABA acts via GABAC receptors to modulate Ca2+ transients evoked by trains of synaptic inputs, but not responses evoked by single stimuli, in myenteric neurons of mouse ileum. Front Physiol. 2018;9:97.

    Article  PubMed  PubMed Central  Google Scholar 

  318. Hampel H, Mesulam MM, Cuello AC, Farlow MR, Giacobini E, Grossberg GT, et al. The cholinergic system in the pathophysiology and treatment of alzheimer’s disease. Brain. 2018;141:1917–33.

    Article  PubMed  PubMed Central  Google Scholar 

  319. Cohen EL, Wurtman RJ. Brain acetylcholine: increase after systemic choline administration. Life Sci. 1975;16:1095–102.

    Article  CAS  PubMed  Google Scholar 

  320. Baik J-H. Dopamine Signaling in reward-related behaviors. Frontiers in Neural Circuits. 2013;7:152.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  321. Nieoullon A. Dopamine and the regulation of cognition and attention. Prog Neurobiol. 2002;67:53–83.

    Article  CAS  PubMed  Google Scholar 

  322. Klein MO, Battagello DS, Cardoso AR, Hauser DN, Bittencourt JC, Correa RG. Dopamine: functions, signaling, and association with neurological diseases. Cell Mol Neurobiol. 2019;39:31–59.

    Article  PubMed  Google Scholar 

  323. Kageyama T, Nakamura M, Matsuo A, Yamasaki Y, Takakura Y, Hashida M, et al. The 4F2hc/LAT1 complex transports L-DOPA across the blood-brain barrier. Brain Res. 2000;879:115–21.

    Article  CAS  PubMed  Google Scholar 

  324. Han W, Tellez LA, Perkins MH, Perez IO, Qu T, Ferreira J, et al. A Neural Circuit for Gut-Induced Reward. Cell. 2018;175:665-678.e23.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  325. Asano Y, Hiramoto T, Nishino R, Aiba Y, Kimura T, Yoshihara K, et al. Critical role of gut microbiota in the production of biologically active, free catecholamines in the gut lumen of mice. American Journal of Physiology-Gastrointestinal and Liver Physiology. American Physiological Society; 2012;303:1288–95.

  326. Hamamah S, Aghazarian A, Nazaryan A, Hajnal A, Covasa M. Role of Microbiota-Gut-Brain Axis in Regulating Dopaminergic Signaling. Biomedicines. Multidisciplinary Digital Publishing Institute; 2022;10:436.

  327. van Kessel SP, Frye AK, El-Gendy AO, Castejon M, Keshavarzian A, van Dijk G, et al. Gut bacterial tyrosine decarboxylases restrict levels of levodopa in the treatment of Parkinson’s disease. Nat Commun. Nature Publishing Group; 2019;10:310.

  328. Fonteh AN, Harrington RJ, Tsai A, Liao P, Harrington MG. Free amino acid and dipeptide changes in the body fluids from alzheimer’s disease subjects. Amino Acids. 2007;32:213–24.

    Article  CAS  PubMed  Google Scholar 

  329. Flanagan E, Müller M, Hornberger M, Vauzour D. Impact of flavonoids on cellular and molecular mechanisms underlying age-related cognitive decline and neurodegeneration. Curr Nutr Rep. 2018;7:49–57.

    Article  PubMed  PubMed Central  Google Scholar 

  330. Krautkramer KA, Fan J, Bäckhed F. Gut microbial metabolites as multi-kingdom intermediates. Nature Reviews Microbiology Nature Publishing Group. 2021;19:77–94.

    Article  CAS  Google Scholar 

  331. Russell WR, Duncan SH, Scobbie L, Duncan G, Cantlay L, Calder AG, et al. Major phenylpropanoid-derived metabolites in the human gut can arise from microbial fermentation of protein. Mol Nutr Food Res. 2013;57:523–35.

    Article  CAS  PubMed  Google Scholar 

  332. Frolinger T, Sims S, Smith C, Wang J, Cheng H, Faith J, et al. The gut microbiota composition affects dietary polyphenols-mediated cognitive resilience in mice by modulating the bioavailability of phenolic acids. Sci Rep. Nature Publishing Group; 2019;9:3546.

  333. Esteban-Fernández A, Rendeiro C, Spencer JPE, del Coso DG, de Llano MDG, Bartolomé B, et al. Neuroprotective effects of selected microbial-derived phenolic metabolites and aroma compounds from wine in human sh-sy5y neuroblastoma cells and their putative mechanisms of action. Front Nutr. 2017;4:3.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  334. Huang Y, Zheng H, Tan K, Sun X, Ye J, Zhang Y. Circulating metabolomics profiling reveals novel pathways associated with cognitive decline in patients with hypertension. Ther Adv Neurol Disord. SAGE Publications Ltd STM; 2020;13:1756286420947973.

  335. Handa AK, Fatima T, Mattoo AK. Polyamines: bio-molecules with diverse functions in plant and human health and disease. Front Chem. 2018;6:10.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  336. Morrison LD, Becker L, Ang LC, Kish SJ. Polyamines in human brain: regional distribution and influence of aging. J Neurochem. 1995;65:636–42.

    Article  CAS  PubMed  Google Scholar 

  337. Tofalo R, Cocchi S, Suzzi G. Polyamines and Gut Microbiota Front Nutr. 2019;6:16.

    PubMed  Google Scholar 

  338. Swann JR, Spitzer SO, Diaz HR. Developmental signatures of microbiota-derived metabolites in the mouse brain. Metabolites. 2020;10:172.

    Article  CAS  PubMed Central  Google Scholar 

  339. Inoue K, Tsutsui H, Akatsu H, Hashizume Y, Matsukawa N, Yamamoto T, et al. Metabolic profiling of Alzheimer’s disease brains. Sci Rep. Nature Publishing Group; 2013;3:2364.

  340. Soda K, Kawakami M. Mediterranean diet and polyamine intake: possible contribution of increased polyamine intake to inhibition of age-associated disease. Nutr Diet Suppl. 2010;3:1.

    Google Scholar 

  341. Kibe R, Kurihara S, Sakai Y, Suzuki H, Ooga T, Sawaki E, et al. Upregulation of colonic luminal polyamines produced by intestinal microbiota delays senescence in mice. Sci Rep. Nature Publishing Group; 2014;4:4548.

  342. Joaquim HPG, Costa AC, Forlenza OV, Gattaz WF, Talib LL. Decreased plasmatic spermidine and increased spermine in mild cognitive impairment and Alzheimer’s disease patients. Arch Clin Psychiatry (São Paulo). Faculdade de Medicina da Universidade de São Paulo; 2019;46:120–4.

  343. Pekar T, Wendzel A, Flak W, Kremer A, Pauschenwein-Frantsich S, Gschaider A, et al. Spermidine in dementia : relation to age and memory performance. Wien Klin Wochenschr. 2020;132:42–6.

    Article  CAS  PubMed  Google Scholar 

  344. Madeo F, Bauer MA, Carmona-Gutierrez D, Kroemer G. Spermidine: a physiological autophagy inducer acting as an anti-aging vitamin in humans? Autophagy. 2018;15:165–8.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  345. Schwarz C, Horn N, Benson G, Wrachtrup Calzado I, Wurdack K, Pechlaner R, et al. Spermidine intake is associated with cortical thickness and hippocampal volume in older adults. Neuroimage. 2020;221: 117132.

    Article  CAS  PubMed  Google Scholar 

  346. Gruendler R, Hippe B, Sendula Jengic V, Peterlin B, Haslberger AG. Nutraceutical Approaches of Autophagy and Neuroinflammation in Alzheimer’s Disease: A Systematic Review. Molecules. 2020;25:6018.

    Article  CAS  PubMed Central  Google Scholar 

  347. Madeo F, Eisenberg T, Pietrocola F, Kroemer G. Spermidine in health and disease. Science. 2018;359:eaan2788.

  348. Misrani A, Tabassum S, Yang L. Mitochondrial Dysfunction and Oxidative Stress in Alzheimer’s Disease. Front Aging Neurosci. 2021;13:617588.

  349. Simpson DSA, Oliver PL. ROS Generation in Microglia: Understanding Oxidative Stress and Inflammation in Neurodegenerative Disease. Antioxidants (Basel). 2020;9:743.

    Article  CAS  PubMed Central  Google Scholar 

  350. De Risi M, Torromino G, Tufano M, Moriceau S, Pignataro A, Rivagorda M, et al. Mechanisms by which autophagy regulates memory capacity in ageing. Aging Cell. 2020;19: e13189.

    PubMed  PubMed Central  Google Scholar 

  351. Doxaki C, Palikaras K. Neuronal mitophagy: friend or foe? Front Cell Dev Biol. 2021;8: 611938.

    Article  PubMed  PubMed Central  Google Scholar 

  352. Puleston DJ, Buck MD, Klein Geltink RI, Kyle RL, Caputa G, O’Sullivan D, et al. Polyamines and eIF5A hypusination modulate mitochondrial respiration and macrophage activation. Cell Metab. 2019;30:352-363.e8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  353. Schroeder S, Hofer SJ, Zimmermann A, Pechlaner R, Dammbrueck C, Pendl T, et al. Dietary spermidine improves cognitive function. Cell Rep. 2021;35: 108985.

    Article  CAS  PubMed  Google Scholar 

  354. Xu T-T, Li H, Dai Z, Lau GK, Li B-Y, Zhu W-L, et al. Spermidine and spermine delay brain aging by inducing autophagy in SAMP8 mice. Aging (Albany NY). 2020;12:6401–14.

    Article  CAS  Google Scholar 

  355. Freitag K, Sterczyk N, Schulz J, Houtman J, Fleck L, Sigrist SJ, et al. The autophagy activator Spermidine ameliorates Alzheimer’s disease pathology and neuroinflammation in mice. bioRxiv. Cold Spring Harbor Laboratory; 2020;2020.12.27.424477.

  356. Maglione M, Kochlamazashvili G, Eisenberg T, Rácz B, Michael E, Toppe D, et al. Spermidine protects from age-related synaptic alterations at hippocampal mossy fiber-CA3 synapses. Sci Rep. Nature Publishing Group; 2019;9:19616.

  357. Schwarz C, Stekovic S, Wirth M, Benson G, Royer P, Sigrist SJ, et al. Safety and tolerability of spermidine supplementation in mice and older adults with subjective cognitive decline. Aging (Albany NY). 2018;10:19–33.

    Article  CAS  Google Scholar 

  358. Wirth M, Benson G, Schwarz C, Köbe T, Grittner U, Schmitz D, et al. The effect of spermidine on memory performance in older adults at risk for dementia: a randomized controlled trial. Cortex. 2018;109:181–8.

    Article  PubMed  Google Scholar 

  359. Wirth M, Schwarz C, Benson G, Horn N, Buchert R, Lange C, et al. Effects of spermidine supplementation on cognition and biomarkers in older adults with subjective cognitive decline (SmartAge)-study protocol for a randomized controlled trial. Alzheimers Res Ther. 2019;11:36.

    Article  PubMed  PubMed Central  Google Scholar 

  360. Pekar T, Bruckner K, Pauschenwein-Frantsich S, Gschaider A, Oppliger M, Willesberger J, et al. The positive effect of spermidine in older adults suffering from dementia: first results of a 3-month trial. Wien Klin Wochenschr. 2021;133:484–91.

    Article  CAS  PubMed  Google Scholar 

  361. Orr ME, Kotkowski E, Bair-Kelps D, Romo T, Espinoza S, Musi N, et al. Results from a pilot study: the effects of nicotinamide riboside on mild cognitive impairment. Alzheimer’s & Dementia. 2020;16: e044746.

    Article  Google Scholar 

  362. Parker A, Fonseca S, Carding SR. Gut microbes and metabolites as modulators of blood-brain barrier integrity and brain health. Gut Microbes. 2019;11:135–57.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  363. Allison AC. The possible role of vitamin K deficiency in the pathogenesis of alzheimer’s disease and in augmenting brain damage associated with cardiovascular disease. Med Hypotheses. 2001;57:151–5.

    Article  CAS  PubMed  Google Scholar 

  364. McCann A, Jeffery IB, Ouliass B, Ferland G, Fu X, Booth SL, et al. Exploratory analysis of covariation of microbiota-derived vitamin K and cognition in older adults. Am J Clin Nutr. 2019;110:1404–15.

    Article  PubMed  PubMed Central  Google Scholar 

  365. Alisi L, Cao R, De Angelis C, Cafolla A, Caramia F, Cartocci G, et al. The relationships between vitamin K and cognition: a review of current evidence. Front Neurol. 2019;10:239.

    Article  PubMed  PubMed Central  Google Scholar 

  366. Kiely A, Ferland G, Ouliass B, O’Toole PW, Purtill H, O’Connor EM. Vitamin K status and inflammation are associated with cognition in older Irish adults. Nutr Neurosci. 2020;23:591–9.

    Article  CAS  PubMed  Google Scholar 

  367. Tamadon-Nejad S, Ouliass B, Rochford J, Ferland G. vitamin K deficiency induced by warfarin is associated with cognitive and behavioral perturbations, and alterations in brain sphingolipids in rats. Front Aging Neurosci. 2018;10:213.

    Article  PubMed  PubMed Central  Google Scholar 

  368. Soutif-Veillon A, Ferland G, Rolland Y, Presse N, Boucher K, Féart C, et al. Increased dietary vitamin K intake is associated with less severe subjective memory complaint among older adults. Maturitas. 2016;93:131–6.

    Article  CAS  PubMed  Google Scholar 

  369. Bray N. The microbiota–gut–brain axis. Nature Research: Nature Publishing Group; 2019.

    Google Scholar 

  370. Ticinesi A, Nouvenne A, Tana C, Prati B, Meschi T. Gut microbiota and microbiota-related metabolites as possible biomarkers of cognitive aging. Adv Exp Med Biol. 2019;1178:129–54.

    Article  CAS  PubMed  Google Scholar 

  371. Kurbatova N, Garg M, Whiley L, Chekmeneva E, Jiménez B, Gómez-Romero M, et al. Urinary metabolic phenotyping for Alzheimer’s disease. Scientific Reports. Nature Publishing Group; 2020;10:21745.

  372. Fiandaca MS, Zhong X, Cheema AK, Orquiza MH, Chidambaram S, Tan MT, et al. Plasma 24-metabolite panel predicts preclinical transition to clinical stages of alzheimer’s disease. Front Neurol. 2015;6:237.

    Article  PubMed  PubMed Central  Google Scholar 

  373. Casanova R, Varma S, Simpson B, Kim M, An Y, Saldana S, et al. Blood metabolite markers of preclinical alzheimer’s disease in two longitudinally followed cohorts of older individuals. Alzheimer’s & Dementia. 2016;12:815–22.

    Article  Google Scholar 

  374. de Leeuw FA, Peeters CFW, Kester MI, Harms AC, Struys EA, Hankemeier T, et al. Blood-based metabolic signatures in alzheimer’s disease. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring. 2017;8:196–207.

    Google Scholar 

Download references

Acknowledgements

Figures created with BioRender.com.

Funding

Not applicable.

Author information

Authors and Affiliations

Authors

Contributions

EC and GLG wrote the manuscript. MP, MM, SS, GC, JC and DV edited and critically reviewed the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to David Vauzour.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Connell, E., Le Gall, G., Pontifex, M.G. et al. Microbial-derived metabolites as a risk factor of age-related cognitive decline and dementia. Mol Neurodegeneration 17, 43 (2022). https://doi.org/10.1186/s13024-022-00548-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13024-022-00548-6

Keywords