Another advantage of connectoon Dehydration and dizziness -omics domains would be improved mechanistic insight into the human gut-brain axis. J Alzheimers Dis. Read about the first ten years of study.

Gut-brain axis connection -

It is the primary neurotransmitter of the parasympathetic nervous system, a part of the autonomic nervous system a branch of the peripheral nervous system related to regulating automatic body processes such as digestion and breathing.

It plays a role in contracting smooth muscles and dilating blood vessels. It also increases bodily secretions and slows the heart rate. It also is involved in various mental processes, such as memory and cognition. Imbalances in acetylcholine have been linked to dementia and Alzheimer's disease.

Acetylcholine is synthesized from the nutrient choline. Like the previous neurotransmitters, acetylcholine must be synthesized in the brain from choline transported through carriers in blood cells. Acetylcholine has been shown to be produced by multiple bacteria in the gut, including Bacillus acetylcholine.

Lactobacillus plantarum, Bacillus subtilis, Escherichia coli, and Staphylococcus aureus. subtilis forms larger quantities of acetylcholine than E. coli or S. This form of acetylcholine acts in the enteric and peripheral nervous systems.

The fascinating role that inflammation plays in psychiatry has recently received increasing attention. Studies have established a link between higher inflammatory markers and their metabolites and depression.

It has also been demonstrated that the administration of inflammatory triggers has been associated with the development of depressive symptoms. These inflammatory mediators have the potential to interact within multiple pathways that can result in mood shifts and depression.

These include their effects on monoamine neurotransmitter metabolism, neuroendocrine function, synaptic plasticity in the neurons, and the various neurocircuits related to mood regulation. For these reasons, pharmacological treatments that aim at modulating inflammatory mediators have been under investigation for the treatment of depression.

Various factors such as psychosocial stress, diet, inflammatory adipose tissue, a leaky gut, and an imbalance between regulatory and pro-inflammatory T cells can all contribute to inflammation in the brain.

This low-grade chronic neuroinflammation is believed to play a crucial role in forming a basis for the interaction between psychological stress, impaired gut microbiota, and major depressive disorder.

Microbes can produce metabolites that enter circulation, alter the inflammatory tone in the gut, periphery, and central nervous system CNS , and signal the trafficking of immune cells into the brain.

Furthermore, the vagus nerve has been shown to modulate brain immune responses. Some specific bacteria in the gut have been shown to have an essential role in the immune response, including inflammation.

This is more evidence of when dysbiosis an imbalance in commensal microbes, including an overgrowth of pathogens can cause inflammation in the gut and eventually lead to a leaky gut , causing systemic inflammation. Gut dysbiosis and leaky gut have both been linked to psychiatric disorders.

Assessing for dysbiosis and digestive health is imperative to establish a healthy microbiome that can foster a balanced mood via the gut-brain connection. Comprehensive stool tests offer a complete look at gut health by measuring pathogens and analyzing digestion, nutrient absorption, inflammation, and immune function, all of which impact the gut-brain axis.

Due to the bi-directional relationship between the gut and the brain, calming the mind by supplying it with proper neurotransmitter balance can modulate mood and may impact the gut through the vagus nerve pathway. Vibrant Wellness Neurotransmitters analyzes over 30 molecules associated with the neurotransmitter's groups of amines, amino acids, organic acids, and others.

Over time, micronutrient-related malnutrition can lead to mental health and mood disorders. Micronutrients serve as cofactors in enzymes that help produce amino acids and neurotransmitter formation in the gut and brain.

The Cellular Micronutrient Assay by Cell Science Systems includes measurements of nutrients implicated in balancing mood, including B vitamins. A large body of research demonstrates correlations between essential fatty acids, brain development, and mood and behavior outcomes.

Furthermore, lower levels of omega-3s have been shown to impact the brain's dopaminergic centers. Omega-3s are also being studied for their role in serotoninergic signaling. Finally, they play a role in modulating inflammation affecting mental health , and fatty acids have been linked to microbiota diversity.

In a recent review , B vitamins were also shown to modulate stress response and benefit people at risk for mood issues due to deficiencies.

In one study, vitamin B6 was shown to reduce anxiety symptoms believed to be related to its role in GABA production. Magnesium supports nerve transmission and neuromuscular conduction and plays a protective role against excessive neural excitation.

Magnesium levels have been linked to various mental and neurological health conditions. Foods high in magnesium include:. Fermented foods , such as yogurt, kefir, kimchi, tempeh, and sauerkraut, contain microbes that support healthy brain activity.

High fiber foods, including whole grains, fruits, vegetables, nuts, and seeds, contain prebiotics which are good for your bacteria and help to produce short-chain fatty acids. Fiber is a form of prebiotics that can feed the bacteria that modulate brain activity and neural signaling.

Polyphenol-rich foods, including cocoa , green tea, olive oil, and coffee, contain plant chemicals digested by your gut bacteria to support healthy microbe balance and brain health.

Several studies have supported the role of probiotics in modulating mood and brain health. A more recent study showed that an eight-strain probiotic supplemented with treatment as usual TAU produced better results than TAU and placebo for depression. Finally, in another study , "probiotic administration for four weeks was associated with changes in brain activation patterns in response to emotional memory and emotional decision-making tasks, which were also accompanied by subtle shifts in gut microbiome profile.

Specific probiotics have been labeled " psychobiotic ," "a live organism that, when ingested in adequate amounts, produces a health benefit in patients suffering from psychiatric illness.

Recently it was found that there is an interaction between the gut microbiota and herbal medicines through two pathways. First, the gut microbiota "digests" the herbal medicines into absorbable, active small molecules which produce biological changes.

Secondly, herbal medicines alter the composition of the gut microbiota and its secretions, leading to physiological changes. For example, many herbs contain polysaccharides which cannot be digested by regular digestive processes.

Therefore, specific microbes, such as Bifidobacterium and Bacteroides, can secrete various enzymes to break them down into smaller metabolites that can have various impacts on the body.

Some herbs that have shown to benefit mood include ashwagandha for stress and anxiety , St. John's Wort for depression showing superiority to placebo and equal effectiveness to medications , Rhodiola for stress and depression, and saffron for depression Supplements to support mood that also supports the gut include the nutrients mentioned above: b-vitamins , and precursors, magnesium 36 , and fish oils Exercise has been shown to alter the microbiome and has evidence for changing brain neurochemistry to support mood.

Sleep has been found to alter the microbiome and is very important for overall mental health. At least hours of sleep are optimal for most adults. A recent review found that stress management techniques had beneficial effects on inflammatory activity, anxiety status, and quality of life in IBD patients.

The gut-brain connection significantly impacts irritable bowel disease IBD patients. Our moods are not just stemming from our brains.

We literally have "gut feelings" that are not human-oriented but rather microbial-based. Bi-directional communication from our gut to the brain occurs through various pathways, including how microorganisms produce and assimilate neuroactive compounds, modulate inflammation, and interplay with the vagus nerve.

Integrative medical practitioners can now work with conventional mental healthcare to ensure that the biological and neurological support of the gut-brain is addressed to improve efficacy in treatment.

This can be done through diet, nutrients, herbal approaches, and lifestyle. Cryan JF, O'Riordan KJ, Cowan CSM, Sandhu KV, Bastiaanssen TFS, Boehme M, Codagnone MG, Cussotto S, Fulling C, et al. The Microbiota-Gut-Brain Axis. Physiol Rev. doi: Martin AM, Sun EW, Rogers GB, Keating DJ.

The Influence of the Gut Microbiome on Host Metabolism Through the Regulation of Gut Hormone Release. Front Physiol. Chen Y, Xu J, Chen Y. Regulation of Neurotransmitters by the Gut Microbiota and Effects on Cognition in Neurological Disorders. PMID: Iannone LF, Preda A, Blottière HM, Clarke G, Albani D, Belcastro V, et al.

Microbiota-gut brain axis involvement in neuropsychiatric disorders. Expert Rev Neurother. Breit S, Kupferberg A, Rogler G, Hasler G. Vagus Nerve as Modulator of the Brain-Gut Axis in Psychiatric and Inflammatory Disorders.

Front Psychiatry. Yang, J. The Human Microbiome Project: Extending the definition of what constitutes a human. National Institute of Health: National Human Genome Research Institute. July 16, Top Foods High in Tryptophan. Nourish by WebMD. Accessed September 2, The Enteric Nervous System.

Science Direct. Brennan, D. What to Know About Short Chain Fatty Acids in Food. June 16, Garde S, Chodisetti PK, Reddy M. Peptidoglycan: Structure, Synthesis, and Regulation.

EcoSal Plus. Carpenter, S. That Gut Feeling. The American Psychological Association. September ; 43 8 : Cleveland Clinic. March 18, Strandwitz P. Neurotransmitter modulation by the gut microbiota. Brain Res. Sonne J, Goyal A, Lopez-Ojeda W. In: StatPearls [Internet]. Treasure Island FL : StatPearls Publishing; Jan-.

Cristol, H. What Is Dopamine? June 14, Klein MO, Battagello DS, Cardoso AR, Hauser DN, Bittencourt JC, Correa RG. Dopamine: Functions, Signaling, and Association with Neurological Diseases. Cell Mol Neurobiol.

March 23, Gamma-Aminobutyric Acid GABA. April 25, Rogers, K. acetylcholine: chemical compound. Hammond, N. What to know about acetylcholine. Medical News Today. In addition to cognitive functioning, connectivity may also reflect intrinsic processes, such as emotional and interoceptive awareness [ 8 , 9 ].

The functional and structural connectivity patterns of the brain are affected by numerous genetic and non-genetic interacting factors.

Likewise, the brain can change under the influence of environmental factors. Multiple studies have reported changes in connectivity strength following a mindfulness training, both in structural [ 15 ] and functional connectivity [ 16 ].

Additionally, a systematic review concluded that a lower quality diet was related to decreased structural and functional connectivity of default mode, sensorimotor and attention networks [ 17 ].

Such environmental factors, including diet, may exert their influence on the brain through the gut-brain axis GBA , among others via modulation of the gut microbiota [ 18 ]. The gut microbiota, comprising the trillions of microbes predominantly bacteria residing in the intestines, can modulate gut-brain communication, for example through the production of neuroactive metabolites, and by affecting the integrity of the gastro-intestinal and blood-brain barriers [ 19 , 20 ].

A majority of the studies investigating the microbiota- gut-brain axis MGBA in humans focus on behavioral measures, including clinical diagnoses and questionnaires, providing evidence for a link between the gut microbiota composition and cognitive and emotional functioning [ 21 , 22 , 23 ].

In recent years the number of studies incorporating neuroimaging into the microbiota-gut-brain investigation has also increased rapidly. Specifically, the acquisition of functional and structural connectivity data is relatively standardized and often done at rest i. Linking such connectivity measures to the gut microbiota can provide important mechanistic insights into the bi-directional gut-brain communication.

Therefore, we herein systematically review the available studies associating the gut microbiota with brain connectivity, in an effort to evaluate the degree of consistency in this association.

Following PRISMA guidelines, a systematic search on the PubMed database was conducted for reports published up to September 1, The aim was to capture all human studies that 1 collected a fecal sample to assess the gut microbiota, 2 assessed in vivo functional or structural brain connectivity, and 3 performed statistical analysis on the association between the gut microbiota and brain connectivity.

Only peer-reviewed original research studies i. Two independent raters DM, MB reviewed the titles and abstracts and came to a consensus about study inclusion. After inclusion, the following data was independently extracted by two authors DM, MB : demographics, sample characteristics, method of gut microbiota estimation, method of brain connectivity estimation, statistical methods, and relevant results.

Details on the search strategy and study inclusion are provided in Fig. The PRISMA checklist is available in the Supplementary Materials. PRISMA flow diagram detailing the database search, number of reports screened and number of studies included.

The consistency of the findings was assessed on two levels. First, we looked at the gut microbiota and brain connectivity individually.

Second, we assessed the specificity of the microbiota-connectivity association. For the second, the assessment was done by counting the number of studies reporting a statistically significant microbiota-connectivity association and dividing it by the total number of studies that could have identified this association.

Only findings assessed in at least three studies were interpreted. Two authors DM, MB assessed the risk of bias in the included studies using the National Institutes of Health NIH National Health, Lung and Blood Institute Study Quality Assessment Tool for observational Cohort and Cross-sectional Studies [ 24 ].

The tool was modified to also be suitable for case-control and before-after studies with no control group specified in Supplementary Table 3. We used the method section of the STORMS checklist v1. A comprehensive literature search on PubMed yielded reports, of which a total of 19 publications based on 16 unique studies met the inclusion criteria Fig.

Two of the included studies produced more than one publication [ 27 , 28 , 29 ] and [ 30 , 31 ]. For those studies, the findings reported in the individual publications were pooled. There was a wide variation in the target populations.

Eight studies were conducted in healthy individuals [ 27 , 28 , 29 , 32 , 33 , 34 , 35 , 36 , 37 ] including a study conducted in smokers [ 32 ], in newborns [ 36 ], and in infants [ 35 ].

Four of those studies were case-controlled [ 30 , 31 , 38 , 41 , 43 ] and three were longitudinal [ 40 , 44 , 45 ]. All other studies performed associations between gut microbiota composition and brain connectivity based on a single group and timepoint. Further characteristics of the study populations are listed in Table 1.

An overview of the methods and indices used to quantify and analyze the gut microbiota and functional and structural brain connectivity is provided in Fig. Overview of commonly used techniques and indices to investigate the gut microbiota [ 69 , 87 , 88 ] and functional and structural brain connectivity [ 89 , 90 , 91 , 92 ].

The included studies employed various sequencing workflows to estimate the gut microbiota composition. Three studies performed shotgun metagenomic sequencing [ 36 , 38 , 45 ], while all other studies performed 16s rRNA gene sequencing.

Three studies performed microbiota-based clustering [ 27 , 28 , 30 , 31 , 34 ], and all but two studies assessed microbial abundance. Additional methodological information regarding sample collection and data processing is presented in Table 2. Fourteen out of sixteen studies assessed functional connectivity, of which twelve used resting-state functional magnetic resonance imaging rs-fMRI , one used task-based fMRI [ 33 ], and one used resting-state functional near-infrared spectroscopy fNIRS [ 36 ].

Four out of fourteen studies assessed structural connectivity using diffusion tensor imaging DTI [ 28 , 34 , 39 , 40 ]. Additional information about the metrics used to compute connectivity, and the a priori selection of brain regions, networks, or white matter tracts for each study is provided in Table 2.

Three studies used packages for differential abundance testing, including sparse partial least squares discriminant analysis sPLS-DA [ 34 , 44 ], linear discriminant analysis effect size LefSE [ 36 ], microbiome multivariable association with linear models MaAsLin2 [ 36 ], and differential gene expression analysis based on the negative binomial distribution DESeq2 [ 44 ].

Finally, linked ICA [ 37 ], spatial canonical correlation analysis sCCA [ 33 ] and Parametric Empirical Bayes PEB [ 33 ] analysis were employed by one study each.

Results on the microbiota level are discussed first, starting with findings in alpha- and beta diversity, followed by findings in microbial composition clusters and abundance.

Next, results on the brain connectivity level are discussed, starting with findings in functional connectivity, followed by findings in structural connectivity. Finally, the specificity of the association between the microbiota and connectivity is discussed.

A detailed summary of the findings per individual study is available in the Supplementary Materials. All six studies assessed a measure of alpha diversity Shannon or Simpson , of which four studies reported an association with at least one brain connection or network [ 27 , 28 , 29 , 33 , 35 , 36 ] Fig.

Only one study assessed a measure of beta diversity weighted UniFrac , and reported an association with functional brain connectivity [ 32 ].

As there is only one study assessing this, it does not warrant interpreting at this stage Supplementary Table 1. A comprehensive overview of the results per study can be found in Table 3.

Graphic summary of the reported associations between microbial diversity and functional connectivity A , and between microbial abundances and functional connectivity B.

Each connection in the chord diagram reflects a reported association between the abundance of that genus or diversity measure and functional connectivity. Of note, the graphical overview displays the absolute number of reported associations, skewing it towards genera and connectivity networks that are studied more frequently a consequence of the selection bias in the reported studies.

ACC anterior cingulate cortex, DMN default mode network, ECN executive control network, FPN frontoparietal network, SMN sensorimotor network, SN salience network. Of those, two studies identified two clusters: one high in Bacteroides and one high in Prevotella [ 30 , 31 , 34 ].

One study identified three clusters: a Bacteroides -high, Prevotella -high, and Ruminococcus -high cluster [ 27 , 28 , 29 ]. All three studies reported at least one association with connectivity, either functional [ 27 , 28 , 29 , 30 , 31 ] or structural [ 28 , 29 , 34 ] see Table 3.

Given the low number of studies, variability in number of clusters, and uncertainty about what the clusters consist of, it remains difficult to interpret the findings and draw conclusions about potential consistency Supplementary Table 1.

The genera Bacteroides , reported in nine out of eleven studies [ 32 , 33 , 36 , 37 , 38 , 40 , 42 , 43 , 44 ], and Prevotella , reported in six out of ten studies [ 30 , 31 , 32 , 34 , 36 , 37 , 38 ], were most consistently associated with brain connectivity.

Additionally, genera within the order Clostridiales were also repeatedly reported in association with brain connectivity. Within this order, the genus Ruminococcus was most consistently reported in four out of seven studies [ 30 , 31 , 33 , 37 , 44 ] , followed by Blautia in three out of five studies [ 37 , 38 , 41 ].

Other studies meeting the criteria for consistency include Collinsella three out of five studies [ 30 , 36 , 38 ] , Enterococcus [ 36 , 38 ], and Alistipes [ 38 , 44 ] each reported in two out of five studies and Bifidobacterium two out of three studies [ 36 , 37 ].

These genera were associated with regions distributed throughout the brain, both on a region-to-region and network level. Fourteen out of sixteen studies assessed the association between functional connectivity and the gut microbiota, either employing a seed-based i.

resting-state networks approach. All functional connections, seed-based and ICA-based were aggregated to a network level to improve interpretability Supplementary Table 2. Salience network connectivity was consistently reported in association with the gut microbiome nine out of ten studies.

Particularly the connectivity of the anterior cingulate cortex ACC [ 27 , 28 , 29 , 30 , 31 , 33 , 35 , 37 , 38 ] and insula [ 27 , 28 , 29 , 32 , 33 , 35 , 38 , 41 ] each reported in six out of eight studies were frequently reported.

Additionally, amygdala connectivity three out of six studies [ 30 , 31 , 35 , 38 ] and ICA-based salience network connectivity two out of three studies [ 37 , 38 ] met the criterion of consistency on the brain connectivity level.

The default mode network DMN was reported in association with the gut microbiota in seven out of nine studies: six out of six studies reported associations between ICA-based DMN-connectivity and the gut microbiota [ 27 , 28 , 29 , 30 , 31 , 36 , 37 , 38 , 42 ], and associations with the precuneus were reported in three out of six studies [ 27 , 28 , 29 , 38 , 44 ].

Finally, the frontoparietal network FPN was consistently associated with the gut microbiota reported in seven out of nine studies. Particularly, ICA-based FPN-connectivity four out of four studies [ 27 , 28 , 29 , 36 , 37 , 38 ] and connectivity of the dorsolateral prefrontal cortex three out of six studies [ 27 , 28 , 29 , 38 , 42 ] and inferior parietal lobe two out of four studies [ 30 , 31 , 35 ] were reported with higher frequency.

Finally, regions within the sensorimotor network were reported in four out of seven studies no specific regions within this network [ 27 , 28 , 29 , 35 , 38 , 41 ] and the superior temporal gyrus was associated with the gut microbiota in three out of six studies [ 27 , 28 , 29 , 38 , 40 ].

These connectivity networks were exhibiting associations with a wide range of diversity indices and genera abundances. A comprehensive overview of the findings per study can be found in Table 3 and Supplementary Table 2. Three out of sixteen studies assessed structural connectivity, all of which reported at least one association with gut microbiota diversity or composition [ 28 , 29 , 34 , 39 ].

However, the small number of studies and the variability in how structural connectivity was quantified and labeled, precludes meaningful interpretation at this time Table 3 , Supplementary Table 1. Despite observing recurring patterns in findings on the gut microbiota and brain connectivity level, patterns are not evident in the association between microbiota and connectivity.

None of the microbiota-connectivity associations were reported in at least fifty percent of the studies, thus not meeting the consistency criterion. Instead, diversity indices and microbial abundances were associated with a widespread set of brain regions and networks without any discernible pattern emerging.

That is, the association between the gut microbiota and brain connectivity was non-specific Fig. The primary source of bias was related to incomplete reporting of the methods, including a lack of detail in the description of the recruitment procedure, microbiota data handling, and description of the used statistical methods.

Additionally, about a third of the studies did not correct for the effects of key confounders i. The quality assessment and explanatory notes per study are shown in Supplementary Table 6.

A qualitative systematic synthesis of the available study findings shows associations between the gut microbiota and brain connectivity. On the microbiota level, a majority of the studies reported an association between microbial richness or diversity and connectivity.

In terms of genus abundance, the genera Bacteroides , Prevotella , Ruminococcus , Blautia , and Collinsella were reported with the highest consistency, followed by the genera Enterococcus , Alistipes , and Bifidobacterium.

For functional brain connectivity, the highest level of consistency was found for the DMN, FPN, and salience network particularly the insula and ACC. There were too few studies assessing microbial clusters or structural connectivity to draw definite conclusions at this time.

Moreover, although some microbial genera or brain networks were reported with higher frequency, there was no specificity in the association between the gut microbiome and brain connectivity, and a majority of the findings, both in microbiota and brain, were inconsistent and poorly or not replicated across studies.

Consequently, the conclusion is limited to the observation of a potential association between the gut microbiota and brain connectivity. Finally, the studies differed in their target population, focusing on a range of different diseases.

Considering the large methodological differences between studies as well as a lack of direct comparisons between the case and control participants, is presently not possible to draw conclusions about differences in the microbiota-connectivity associations between cases and controls or between different disease populations.

Below we will first discuss the findings in relation to neurocognitive functioning and possible functional mechanisms. Finally, we will address study aspects that can explain inconsistencies in the findings, and which need to be considered to further advance the field.

The current findings suggest an involvement of brain networks involved in emotion-related cognition and executive functioning. The association between the gut microbiota and emotion-related functioning is a recurring topic in gut-brain research.

Several of the included studies found associations between the microbiota composition and levels of anxiety, depression, or negative affect, measured using questionnaires [ 30 , 31 , 34 ].

Moreover, several of the brain structures associated with the gut microbiota have a putative emotion-related function. For example, the insula, whose connectivity was associated with alpha diversity [ 32 , 33 , 35 ] and with the abundance of the genera Roseburia and Bacteroides [ 28 , 32 , 41 ], is involved in socio-emotional processing, and insular brain damage can result in apathy and anxiety [ 47 ].

Moreover, the insula is involved in interoception, both emotional and visceral [ 8 , 9 ]. Finally, the DMN, whose connectivity was associated with microbial diversity and the abundance of a wide range of bacterial genera Fig. Moreover, DMN connectivity is altered in depression, a disorder characterized by impairments in emotion regulation [ 50 ].

Interestingly, Kelsey and colleagues [ 36 ] reported that stronger intranetwork connectivity of the homologous-interhemispheric network in newborns mediated the association between higher alpha diversity and behavioral temperament, behavior that is predictive of anxiety and depression in adulthood [ 51 ].

Another set of findings suggests that the gut microbiota may be associated with executive functioning. Cai and colleagues [ 27 ] reported that higher internetwork connectivity between the FPN and visual networks and lower internetwork connectivity between the dorsal attention, and visual networks mediated the association between higher alpha diversity and better working memory and attention.

In addition, the association between Prevotella- , Bacteroides- , and Ruminococcus -high clusters and response inhibition was mediated by connectivity of the orbitofrontal cortex part of the FPN , a region involved in emotional decision making [ 52 ].

Specifically, individuals in the Prevotella and Ruminococcus -high clusters exhibited stronger orbitofrontal connectivity, which was associated with poorer response inhibition. Consistent with these findings, several functional networks associated with gut microbiota diversity are involved in executive functioning.

For example, the FPN or its individual constituents was associated with the abundance of, among others, the genera Prevotella , Bacteroides , and Blautia [ 36 , 37 , 46 ]. This network is mainly involved in executive control, encapsulating processes related to response inhibition, attention, and working memory [ 6 , 53 ].

Altogether, the associations between the gut microbiota and the brain, described in this review, indirectly link the gut microbiota with processes related to emotion and executive functioning through brain connectivity patterns. However, in the absence of direct, empirically tested, associations with cognition and behavior, this should be interpreted with caution.

These speculations should be validated using, for example, larger-scale mediation analyses to disentangle the intermediate role of brain connectivity in the association between the gut microbiota and behavior. Up to now, studies mostly report taxonomic findings, which are not appropriate to deduce functional pathways.

Nevertheless, we can still leverage the findings from previous studies to speculate about potential mechanisms, which can be used as hypothesis-generating ideas as the field moves towards more function-focused microbiome research.

Based on the taxonomic findings, one possible communication pathway would be through the production of short-chain fatty acids SCFAs; e.

For example, species within the genera Prevotella and Bacteroides , whose abundances on a genus level were associated with connectivity of a widely distributed set of brain regions and networks Fig. Moreover, species in the genus Blautia , whose abundance on a genus level was associated with the connectivity of sensorimotor regions as well as network connectivity of the DMN and executive control network, are described to have propionate-producing properties [ 54 ].

Finally, species in the genus Roseburia , whose abundance on a genus level was associated with insular, amygdala, and DMN connectivity, are among the main butyrate-producing species.

Among others, SCFAs possess the ability to modulate immune activation reviewed in [ 55 ]. In line with this, the association between Roseburia abundance and functional connectivity of the DMN and amygdala, reported by Wang and colleagues [ 30 ] and Zheng and colleagues [ 31 ], was mediated by levels of the pro-inflammatory cytokines interleukin-6 and tumor necrosis factor alpha, suggesting a role for the immune signaling pathway in the microbiota-brain connectivity communication, possibly through the production of butyrate.

The involvement of this pathway may go beyond the gut, as there is preliminary evidence for a role of the immune signaling pathway in the association between functional connectivity and the oral microbiome as well [ 56 ].

Other ways through which gut-synthesized SCFAs may modulate gut-brain communication, and hereby brain connectivity, could be by positively or negatively affecting the integrity of the intestinal and blood-brain barriers [ 55 , 57 , 58 ], or by traveling directly through the blood-brain barrier to the CNS [ 59 , 60 , 61 ], although — similar to the above-suggested role of the SCFAs — evidence directly supporting this is yet lacking.

The gut microbiota may also affect gut-brain communication through the production of neurotransmitters and their precursors [ 46 ].

For example, species within the genera Bacteroides and Bifidobacterium and species within genera Ruminococcus and Blautia , whose abundances were associated with connectivity in a widespread set of brain regions and networks, are major modulators of GABA and serotonin availability in the gut [ 62 , 63 , 64 ].

There are several proposed pathways through which gut-derived neuroactive compounds can affect the brain. For example, there is evidence showing that both GABA and serotonin have immunomodulatory properties [ 65 , 66 ], and both GABA and serotonin receptors have been located on vagal afferents to the CNS, proposing a role for the vagal signaling pathway [ 67 , 68 ].

However, in the absence of direct evidence, the involvement of these pathways remains hypothetical. Altogether, based on the taxonomic findings we can speculate about potential mechanisms. However, most taxonomic findings are reported on a genus level due to the constraints of 16s rRNA sequencing.

A certain genus, and even a single species within a genus, can contribute to multiple metabolite pathways. As such, our speculations should be verified through pathway analysis, preferably using higher resolution metagenomics data coupled with, when possible, bacterial culture-functional studies.

The current review identified several links between microbial genera and brain connectivity, but there is low specificity in the associations between the gut and brain. Additionally, despite identifying some recurring patterns, a majority of the findings, both in microbiota and brain, were inconsistent and poorly replicated across studies.

This may suggest a complex multifaceted relationship between microbial composition and brain connectivity, but it is likely that inconsistencies are at least partially methodology-driven. The limitations identified in this review underscore the need to harmonize the methodological approaches currently applied to microbiome research and functional brain connectivity analysis.

In the following section, we will discuss important study aspects that may explain inconsistencies in the findings, and which need to be considered to further advance the field. The number of studies investigating the microbiota-gut-brain axis is rapidly growing, and in recent years there have been major technological advances in the field.

Nevertheless, there is no golden standard on how to collect, process, and analyze microbiome data. As a result, there is high inter-study variability in laboratory processing e. The number of observed taxa and statistical outcomes can change considerably depending on the collection, storage, bioinformatic pipeline, and statistical test used [ 69 , 70 , 71 , 72 ].

Therefore, to make reliable between-study comparisons it is essential to harmonize the methodological approach. To achieve this, researchers should follow standardized reporting guidelines, such as the STORMS checklist [ 25 ], on how the microbiome data was processed, follow standardized processing pipelines where possible, apply consistent and appropriate statistical approaches for analysis e.

While reducing the multiple comparison problem, additional sources of inter-study variability come from a priori selection of microbial genera and brain regions e. Some of these genera — for example Prevotella and Bacteroides — or brain networks — for example the DMN — are of common interest in studies focusing on the gut-brain communication, increasing the likelihood that the effects are observed or amplified as a result of selection bias.

Moreover, a priori selection, both in taxonomy and brain regions, hinders meaningful comparison between study findings. At the current stage of the field, using a data-driven approach to study the association between the gut microbiota and brain connectivity will help with the identification of patterns of associations in the data without biasing the findings towards pre-existing assumptions.

However, data-driven approaches have a higher risk of identifying spurious associations, and findings may be more challenging to interpret. Therefore, once consistent findings have been established using data-driven approaches, the field could move towards a hypothesis-driven framework that offers clearer research questions and facilitates the interpretation of the findings.

Data analysis should better acknowledge the inherent complexities of both the gut microbiota and brain connectivity data, as this will lead to better integration of the two domains. Both the gut microbiota and the brain are complex systems, characterized by intricate relationships and interconnections [ 73 , 74 ].

At the current time, most studies investigating the association between the gut microbiota and brain connectivity do so using simple bivariate association analyses, even though this is likely an oversimplification of the existing association. As a result, information concealed in the relationship within and between multiple variables i.

Although several studies opted for a multivariate approach for one of the two domains i. The authors identified several multivariate associations between microbial clusters and functional network connectivity. Future studies should make an effort to integrate data from the gut microbiota and brain connectivity.

Possible approaches are the Linked Independent Component Analysis as applied in ref. Moreover, the systems biology approach focuses on multivariate interactions in biological systems rather than exploring each modality in parallel [ 76 ].

There are already different systems biology software programs available [ 77 ]. Nevertheless, the field of human connectomics was already proposed as an extension of systems biology to macroscale neuroscience [ 78 , 79 , 80 ] and could provide insight into the complex microbiota-connectivity interactions.

Another advantage of integrating more -omics domains would be improved mechanistic insight into the human gut-brain axis. There have been numerous studies on possible mechanisms underlying gut-brain communication, both preclinical and in humans reviewed in e.

Usually, mechanisms are studied on a molecular level, without assessing how such processes would affect the brain on a larger scale. To date, only Wang and colleagues [ 30 ] and Zheng and colleagues [ 31 ] explored the mediation effect of immune activation as an underlying mechanism in the gut-brain connectivity association.

Although we can speculate about underlying mechanisms based on taxonomic findings, it would be more informative to directly integrate mechanistic data potentially related to brain connectivity.

For example, metagenomics can complement 16s rRNA sequencing to provide information about the functional potential of the present microbial taxa, metabolomics could provide information about bacterial metabolites that are present in the gut e.

There is currently no agreement on which factors that affect the gut should be considered and corrected for in statistical analyses. This is also reflected in the way studies correct for confounders: approximately two-thirds consider age and sex as key confounders.

Recent antibiotic use is used as an exclusion criterion by three-fourths of the studies, whereas only one study corrects for smoking. To better understand how these factors affect the association between microbiota and brain connectivity, we recommend that future studies conduct sensitivity analyses.

This will — besides establishing the robustness of the findings — help to identify the often environmental factors that influence the association between the gut microbiota and brain connectivity and potentially inform the development of future treatment strategies. Currently, studies assessing the association between the gut microbiota and brain connectivity include a wide range of target populations, from healthy individuals to various disease populations.

While these studies could provide valuable information about disease pathophysiology, the field lacks a reference to which associations in disease populations can be compared. Investigating the microbiota-connectivity associations in large population cohorts can provide such references and aid in the interpretation of study findings.

Moreover, with a case-control study design, it is possible to test differences in the microbiota-connectivity association between groups. However, only one study has performed such analyses [ 41 ], with other studies only focusing on the microbiota-connectivity association in cases.

Performing such comparative analyses will help in clarifying whether there are differences in the associations between different disease populations, and improve our ability to draw meaningful conclusions about group differences.

Once such methodological issues are resolved, it would be valuable to have longitudinal microbiota-connectivity association studies, for example in developing children or elderly individuals, to see how microbial development covaries with neurodevelopment, whether microbiota-connectivity associations vary over time and how this could be related to neurodevelopmental or neurodegenerative disorders.

Most studies discussed here were observational, from which it is not possible to infer causality nor directionality. To advance research on the human MGBA, specifically for the development of gut microbiota-targeting approaches in the treatment of brain-related disorders, it is important to establish causality and directionality.

Assessing directionality and causality in human trials remains a costly challenge, in which randomized controlled trials in combination with appropriate statistical models such as mediation or Mendelian randomization can assist [ 85 , 86 ].

For example, results from mediation analyses point towards gut-to-brain signaling, showing that immune activation one of the MGBA signaling pathways partially mediated the association between microbial abundance and functional brain connectivity [ 27 , 36 ].

Such studies should assess if and how an intervention affects the gut microbiota or brain connectivity, which microbes are causally involved, if intervention-induced changes in the microbiota result in altered brain connectivity, and — importantly — whether this is also reflected in altered cognition and behavior.

In this systematic review, we identified several genera as well as brain regions and networks that were repeatedly associated in microbiota-brain connectivity analyses, showing the potential of employing brain connectivity measures to gain insight into gut-brain communication.

At the same time, there is still limited evidence for specificity in the microbiota-brain connectivity association. Current methodological limitations, including high inter-study variability in methodology and target population, small sample sizes, the a priori selection of microbial genera and brain regions of interest, and the statistical approaches used, introduce bias and thus contribute to the inconsistent findings.

We know the gut-brain communication is multidimensional, and therefore a more systematic and harmonized methodology, which acknowledges this complexity, is key to further unraveling how the gut and brain communicate.

To enhance comparability and replicability, future research should focus on further standardizing processing pipelines and employ data-driven multivariate analysis approaches. Moreover, interventional studies can help to clarify the causality and directionality of the reported findings.

Sporns O, Tononi G, Kötter R. The human connectome: a structural description of the human brain. PLoS Comput Biol. Article CAS Google Scholar. Suárez LE, Markello RD, Betzel RF, Misic B. Linking structure and function in macroscale brain networks.

Trends Cogn Sci. Article PubMed Google Scholar. Damoiseaux JS, Rombouts SARB, Barkhof F, Scheltens P, Stam CJ, Smith SM, et al. Much of the evidence is based on animal research, so it is hard to draw conclusions about how this translates to humans.

It's also hard to establish cause and effect when it comes to the relationship between the gut and the brain. Diversity and balance are hallmarks of a healthy gut microbiome.

Research suggests there might be links between the types of microorganisms in a person's gut and their mental health. A review, published in the journal Pharmacological Research , suggests that poor gut health may contribute to the onset and progression of mental health conditions, including depression and anxiety.

In patients suffering from depressive disorder, levels of Enterobacteriaceae and Alistipes "bad" bacteria were enhanced, whilst the level of Faecalibacterium "good" bacteria was reduced. The researchers also found that there was less diversity in gut bacteria in patients with mental disorders, as well as a decrease in bacteria producing short chain fatty acids.

However, again, it is not clear whether changes in gut bacteria influence mood disorders or vice versa. Probiotics — beneficial bacteria found in fermented foods and dietary supplements — can support gastrointestinal health, according to a meta-analysis published in the journal PLos One.

A promising new field known as psychobiotics is considering the role that probiotics could play in alleviating mental health symptoms. However, further research is needed. Emerging evidence identifies a correlation between the gut microbiome and cognitive performance.

A study, published in the Journal of the International Neuropsychological Society , found a link between gut microbiome composition and cognition in older adults. Individuals with lower proportions of Bacteroidetes and Proteobacteria and higher proportions of Firmicutes and Verrucomicrobia performed significantly better on tests associated with attention, learning and memory.

This article is for informational purposes only and is not meant to offer medical advice. She is a certified personal trainer, nutritionist and health coach with nearly 10 years of professional experience.

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This "gut-brain Dehydration and dizziness has Gut-brwin a popular area cknnection investigation and has aixs immense implications for mental health. It is now Healing vegetable power Gut-brain axis connection there is a distinct biological and axos basis for Guh-brain, neurodevelopmental, connectiin, and neurodegenerative disorders that Natural fat loss journey in the Dehydration and dizziness shifting Dehydration and dizziness Gut-bran of psychiatric illness. In this article, we dive deep into how our gut microbiome affects our mood in both positive and negative ways. This dynamic bi-directional relationship between our bellies and brains is termed the "gut-brain axis. As humans provide a home for the microbes that inhabit the gut, these microorganisms have evolved to return the favor and establish a mutually beneficial symbiotic relationships with their hosts. As they digest our food to meet their own nutritional needs, they also provide energy, nutrients, and neuroactive metabolites, such as neurotransmitters and their precursors, which serve as signaling molecules to the brain. Thank Gug-brain for cohnection nature. You Adis using a browser version with limited support for CSS. Axxis obtain the Gut-brain axis connection experience, we recommend Metabolic syndrome metabolic health use a more connectioon to date browser or turn Connecion compatibility mode in Internet Explorer. In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. A body of pre-clinical evidence shows how the gut microbiota influence brain functioning, including brain connectivity. Linking measures of brain connectivity to the gut microbiota can provide important mechanistic insights into the bi-directional gut-brain communication. In this systematic review, we therefore synthesized the available literature assessing this association, evaluating the degree of consistency in microbiota-connectivity associations.