Gut microbes in neurocognitive and mental health disorders

Figures & data

Figure 1. The Brain-Gut-Microbiome Axis. Depiction of the bidirectional (two-way) communication between the brain and gut through the vagus nerve (A) and the immune system. Communication is achieved through various mechanisms including microbial by-products, such as SCFA, LPS and peptidoglycans (B), release of neurotransmitters (GABA, Norepinephrine, Serotonin, Acetylcholine, and others) and endocrine messengers via the enteroendocrine cells (C) as well as chemokine and cytokine release that can lead to neuroinflammation (D). Stress can influence the microbiota causing dysbiosis leading to an alteration of the immune system, SCFA and tryptophan levels, increasing gut permeability (“Leaky gut) (E) and activation of the HPA axis (F). Adrenocorticotropic hormone (ACTH), Cortisol Releasing Hormone (CRH), Enteroendocrine cells (EEC), y-aminobutyric acid (GABA), Lipopolysaccharides (LPS), Neurotransmitters (NT), Short Chain Fatty Acids (SCFA).

Table 1. Summary of the Microbiome changes in various Mental Health Conditions.

Mental health condition	Study	Change in microbiome	Proposed mechanism of action
Depression	Huang et al. 2018 [164]	Decreased: Firmicutes	Lead to low levels of SCFA and contribute to low-level inflammation.
	Chung et al. 2019 [165]	Increased: Actinobacteria Firmicutes Bifobacterium Blautia Decreased: Prevotella	The process of pentose phosphate, starch, and sucrose metabolism, via microbial functions, play a role in pathways for depression development.
	Naseribafrouei et al. 2014 [97]	Increased: Oscillibacter Alistipes Decreased: Bacteroidetes	Decreased Bacteroidetes have been associated with low-grade inflammation. Alistipes is associated with inflammation and tryptophan availability. Oscillibacter produces valeric which resembles GABA.
	Jiang et al. 2015 [54]	Increased: Bacteroidetes (Proteobacteria, Alistipes) Enterobacteriaceae Decreased: Firmicutes Faecalibacterium Actinobacteria	Proteobacteria can increase gut permeability allowing for gram-negative bacteria to enter systemic circulation. Decreased Firmicutes can lead to decreased SCFA production and intestinal barrier dysfunction.
	Chen et al. 2018 [166]	Increased: Actinobacteria (Female) Decreased: Bacteroidetes (Male)	There were sex differences in gut microbiota compositions in patients with major depressive disorder compared to healthy controls.
	Rong et al. 2019 [167]	Increased: Firmicutes Actinobacteria Bacteriodes Clostridium Bifidobacterium Oscillibacter Streptococcus Decreased: Bacteroidetes	Bacteroidetes may be associated with intestinal inflammation and an indicator of depression-related intestinal inflammation. Bifidobacterium is considered beneficial for the human body and is found in probiotics and helps with SCFA production. Oscillibacter produces valeric acid that resembles GABA and can bind to GABA receptors.
	Aizawa et al. 2016 [168]	Decreased: Bifidobacterium Lactobacillus	Both Bifidobacterium and Lactobacillus have an overall beneficial effect in reducing stress and depressive disorders.
Anxiety	Jiang et al. 2018 [115]	Decreased: SCFA- producing bacteria Increased: Escherichia-Shigella Fusobacterium Ruminococcus gnavus	Decreased SCFA producing bacteria can lead to increased gut permeability. Increased Fusobacterium and Escherichia -Shigella bacteria can lead to systemic inflammation. Ruminococcus gnavus can degrade mucins leading to gut permeability.
	Bailey et al. 2010 [64]	Increase: Clostridium Decrease: Bacteroide	Circulating levels of IL-6 and MCP-1 are increased in stressed mice and correlated to changes to three bacterial genera (i.e., Coprococcus, Pseudobutyrivibrio, and Dorea).
Bipolar disorder	Painold et al. 2019 [126]	Increase: Actinobacteria Coriobacteriia Decrease: Faecalibacterium Ruminococcaceae	Actinobacteria and Coriobacteriia are involved in lipid metabolism with correlation to cholesterol levels. This may correlate to the somatic comorbidities, such as obesity, found in bipolar patients.
	Coello K, et al. 2019 [123]	Increased: Flavonifractor	These bacteria may induce oxidative stress and inflammation in the host.
	Evans et al. 2016 [55]	Decreased: Faecalibacterium	Faecalibacterium has been shown to have anti-inflammatory properties.
	Rong et al. 2019 [167]	Increased: Firmicutes Actinobacteria Bacteriodes Clostridium Bifidobacterium Oscillibacter Streptococcus Escherichia Klebsiella Decreased: Bacteriodetes	Bcteroidetes may be associated with intestinal inflammation and an indicator of depression-related intestinal inflammation. Klebsiella LPS may cause gram-negative induced inflammatory dysregulation, playing a role in MDD pathophysiology.
Schizophrenia	Zhang et al. 2020 [132]	Increased: Proteobacteria Chaetomium Decreased: Faecalibacterium Lachnospiraceae Trichoderma	Lachnospiraceae genera are important for SCFA production and lead to gut permeability allowing opportunistic pathogens, such as Protobacteria to translocate. Faecalibacterium is involved in the direction of gut-naïve CD4 cell differentiation and with underrepresentation can increase gut TH17 cells which can cross the blood-brain barrier and induce abnormal behaviour.
	Zheng et al. 2019 [130]	Decreased: Lachnospiraceae Ruminococcaceae.	Lachnospiraceae and Ruminococcaceae have been linked with the maintenance of gut health.
	Shen et al. 2018 [169]	Increased: Proteobacteria Decreased: Firmicutes	Decrease in Firmicutes, such as Blautia, Coprococcus, and Roseburia lead to decreased SCFA production.
Post-traumatic stress disorder	Hemmings et al. 2017 [137]	Decreased: Actinobacteria Lentisphaerae Verrucomicrobia	Reduced levels of the Akkermansia muciniphila, part of the Verrucomicrobia phyla can lead to a decrease in anti-inflammatory properties. It is also found that there is a decrease in CD4+ T cells leading to a dysregulation of the immune system and HPA axis.
Obsessive-compulsive disorder	Rao et al. 2015 [108]	Increased levels of cytokines and chemokines	Increased levels of IL-2, IL-4, IL-6, IL-10, and TNF-α suggesting alteration in the inflammatory and HPA axis response. As well, treatment with prebiotics containing L. belveticus and B. longum reduced symptoms suggesting the role of microbial dysbiosis.
Dementia	Vogt et al. 2017 [78]	Increased: Bacteroidetes Decreased: Firmicutes Bifidobacterium	Increased gram-negative bacteria along with increased gut permeability can lead to translocation of LPS into systemic circulation and contribute to AD pathology through inflammation.
	Zhuang et al. 2018 [170]	Increases: Actinobacteria Decreased: Bacteroidetes	Changes in neuro-inflammation leading to a deposition of beta-amyloid in the brain.
	Li et al. 2019 [80]	Increased: Escherichia Blautia Bifidobacterium Streptococcus Lactobacillus Dorea genus.	Brain tissue from AD patients showed LPS and E. coli colocalized with amyloid plaque. Suggest microbiota dysbiosis may trigger amyloid pathogenesis along with systemic inflammation impairing the blood-brain barrier. May further lead to neuroinflammation and neurodegeneration.
	Saji et al. 2019 [81]	Increased: Bactoides	Increased prevalence of Bacteroides is independently associated with the presence of MCI patients.

AD: Alzheimer’s dementia; GABA: gamma aminobutyric acid; HPA: hypothalamic pituitary adrenal; IL: interleukin; LPS: lipopolysaccharide; MCI: mild cognitive impairment; MDD: major depressive disorder; MCP: monocyte chemoattractant protein; SCFA: short chain fatty acid; TNF-α: tumour necrosis factor alpha.

Table 2. Human studies of gut microbiota changes in various mental health conditions.

Condition	Study	Bacterial Difference and Significance
Anxiety	Jiang et al. 2018 [115] GAD (n = 40) HC (n = 36)	There is a marked decrease in microbial richness in patients with GAD, especially reduced SCFA producing bacteria. Compared to HCs, Firmicutes spp. were decreased (p < .05) while Fusobacteria and Bacteroidetes were increased (p < .05) in GAD patients. At the genus level, Bacteriodetes, Ruminococcus gnavus, and Fusobacterium were decreased (p < .05) in GAD patients while Faecalibacterium, Eubacterium rectale, Sutterella (p < .02), Lachnispira and Butyricicoccus (p < .05) were increased in HC.
	Chen et al. 2019 [171,172] GAD (n = 36) HC (n = 24)	Patients with GAD were found to have increased abundance of Bacteroidaceae, Enterobacteriaceae, and Burkholderiaceae (p < .05). The HCs showed higher abundance of Prevotellaceae (p < .01), Muribaculaceae (p < .05), Succinivibronaceae (p < .01), Mollicutes_PF39_norank (p < .001). A negative correlation was found between the abundance of Eubacterium_coprostanoligenes_group, Ruminococcaceae_UCG-014, and Prevotella_9 and anxiety severity. A positive correlation was found between anxiety severity and Bacteroides and Escherichia-Shigella abundance.
	Bruch et al. 2016 [114] Dataset offers records of 94,407 individuals	Individuals with an intestinal infection in Round 1 had an OR 1.34 (95% CI 1.10–1.64, p =  < .01) of developing anxiety in future rounds.
PTSD	Hemmings et al. 2017 [137] PTSD (n = 18) TE (n = 12)	Microbial diversity estimates were similar between PTSD and TE individuals. Random forest analysis showed PTSD was linked to decreased Actinobacteria, Lentisphaerae, and Verrucomicrobia abundance (p = .035).
Depression	Huang et al. 2018 [164] MDD (n = 27) HC (n = 27)	Patients with MDD were found to have lower alpha diversity in the microbiome compared to HC. Using the Wilcox test, the study showed significant decrease of Firmicutes phylum (p < .001) in MDD subjects.
	Stevens et al., 2018 [173] DEP/ANX (n = 22) HC (n = 28)	The plasma levels of LPS (p = .014), zonulin (p < .001) and FABP2 (p < .032) showed significant elevation in DEP/ANX compared to HC using ANOVA. (FABP2 and zonulin are biomarkers of gut epithelium tight junction barrier integrity). This suggests that there is increased gut permeability in DEP/ANX.
	Kelly et al. 2016 [91] DEP (n = 34) HC (n = 33)	In DEP the relative abundance of Prevotellaceae (U = 355, p = .007) was decreased, while Thermoanaerobacteriaceae (U = 52.5, p = .021) was increased (at the Family level) compared to HC. When examining bacteria at the genus level, there was an increase relative abundance of Eggerthella (U = 21.0, p = .009), Holdemania (U = 146.5, p = .023), Gelria (U = 52.5, p = .021), Turicibacter (U = 89, p = 0.034), Paraprevotella (U = 119, p = .041), and Anaerofilum (U = 50.5, p = .021) while Prevotella (U = 324.5, p = .022) and Dialister (U = 153.5, p = .032) were decreased when comparing DEP to HCs.
	Lin et al. 2017 [174] MDD (n = 10) HC (n = 10)	Patients with MDD were found to have lower abundance of the phylum Bacteroidetes (p < .01) and higher Firmicutes (p < .01) compared to HC using the student T test. At the genus level, MDD patients had higher Prevotella (p < .01), Klebsiella (p < .01), Streptococcus (p < .01), and Clostridium X1 (p < .01) compared to HC using the Wilcoxon Sign Rank test.
	Chen et al. 2018 [96] MDD (n = 10) HC (n = 10)	It was found that Firmicutes and Actinobacteria were more abundant (p < .05) while Bacteroidetes and Proteobacteria were less abundant (p < .05) in MDD patients compared to HC using Mann- Whitney test.
	Chung et al.2019 [165] MDD (n = 36) HC (n = 37)	There was significant microbiota difference between the MDD and HC populations (p < .001) using ANCOM. The phylum Actinobacteria and Firmicutes were overrepresented in MDD patients. At the genus level, Bifidobacterium and Blautia were high in MDD while HC showed higher levels of Prevotella.
	Chen et al.2018 [166] MDD (male) (n = 20) MDD (female) (n = 24) HC (male) (n = 20) HC (female) (n = 24)	In female patients, the relative abundance of Actinobacteria in those with MDD was increased compared to HC using beta diversity measures. For the male individuals, there was a decrease of Bacteroidetes in those with MDD compared to HC. The results suggested there were differences in the dominant phenotype between male and female patients with MDD.
	Aizawa et al.2016 [168] MDD (n = 43) HC (n = 57)	Patients with MDD had lower Bifidobacterium (p = .012) and Lactobacillus (p = .067) counts compared to HCs. Individuals whose bacterial counts were below the cut-off points of 9.53 and 6.49log 10 cells/g for Bifidobacterium and Lactobacillus, respectively were more common in MDD patients (Bifidobacterium: OR 3.23, 95% confidence interval [CI] 1.38–7.54, p = .010; Lactobacillus: OR 2.57, 95% CI 1.14–5.78, p = .027).
	Jiang et al. 2015 [54] MDD (n = 46) A-MDD (n = 29) R-MDD (n = 17) HC (n = 30)	Patient with A-MDD showed increased Bacteroidetes, Fusobacteria, and Proteobacteria (p < .05) and decreased Firmicutes and Actinobacteria (p < .05) compared to HCs. Individuals with R-MDD had increased Bacteroidetes and Proteobacteria (p < .05) and decreased Firmicutes, Fusobacteria, and Actinobacteria (p < .05) compared to HCs. A negative correlation between the relative abundance of Faecalibacterium and MDD symptoms was found (p < .05) using alpha diversity and beta diversity measures.
	Zheng et al. 2016 [94] MDD (n = 38) HC (n = 63)	Increased Actinobacteria and decreased Bacteroidetes (p < .01) in patients with MDD compared to HC using phylogenetic beta diversity analysis. Faecal microbiota transplant of MDD samples into GF mice caused depression-like behaviours in 2 weeks post transplant.
	Naseribafrouei et al. 2014 [97] MDD (n = 37) HC (n = 18)	Patients with depression showed an underrepresentation of the Bacteroidetes phylum with decreased order Bacteroidales (p = .05). The genus Oscillibacter (p = 0.03) and Alistipes (p = .007) were increased and showed a significant association with depression using PLS‐DA.
Dementia	Li et al. 2019 [80] AD (n = 30) MCI (n = 30) HC (n = 30)	Study found that patients with MCI and AD show microbial dysbiosis compared to health controls. In particular, AD patients showed increased Escherichia (β =  1.27 [95% CI, 0.64–1.90], p < .001), Blautia (β = 12.82 [95%CI, 5.11–20.53], p = .001), Bifidobacterium (β = 4.61 [95%CI, 1.67–7.74], p = .002), Streptococcus (β = 3.28 [95%CI, 1.17–5.39, p = .002), Lactobacillus (β = 3.41 [95%CI, 0.49–6.34], p = .022), and Dorea genus (β = 9.75 [95%CI, 0.48–19.01], p = .039) using multivariate regression analysis.
	Zhuang et al. 2018 [170] AD (n = 43) HC (n = 43)	When compared to HCs, there was an increased abundance of Bacteroidetes (p < .05) and decreased abundance of Actinobacteria (p < .05) in AD patients. At the genus level, AD patients showed an increased abundance of Subdoligranulum (p < .01) and decreased Bacteroides (P < .01) and Lachnoclostridium (p < .001) compared to HCs. Analysis was done using alpha and beta diversity measures.
	Vogt et al. 2017 [78] AD (n = 25) HC (n = 25)	AD participants showed decreased abundance of Firmicutes and Actinobacteria, and increased abundance of Bacteroidetes compared to HC participants (p < .05). Analysis was done using alpha and beta diversity metrics.
	Saji et al. 2019 [81] MCI (n = 61) HC (n = 21)	Patients with MCI had more enterotype I microbes and fewer enterotype III microbes (p = .009) compared to HC suggesting a prevalence of Bacteroides. In addition, multivariate analysis showed enterotype III microbes were significantly associated with MCI (OR 0.19, 95% CI, 0.05–0.65, p = .008)
Schizophrenia	Zhang et al. 2020 [132] SCZ (n = 10) HC (n = 16)	Chinese patients with Schizophrenia were found to have increased harmful Proteobacteria and decreased Faecalibacterium and Lachnospiraceae genera (which are important for SCFA production). Schizophrenia patients also had higher Chaetomium and lower Trichoderma levels compared to HC. Analysis was done with LDA scores as well as using alpha and beta diversity measures.
	Zheng et al. 2019 [130] SCZ (n = 63) HC (n = 69)	There were alterations of the gut microbiota in SCZ patients with less diverse population based on Shannon and Choa indices. In SCZ there were 54 OTUs decreased compared to HCs, with the dominant bacterial families identified as Lachnospiraceae (16 OTU) and Ruminococcaceae (12 OTU) using alpha diversity analysis as well as PLS-DA.
	Shen et al. 2018 [169] SCZ (n = 64) HC (n = 53)	In SCZ patients there is an increased abundance of the Proteobacteria phylum. At the genus level using the Welch's t-test the relative abundance of Succinivibrio, Megasphaera, Collinsella, Clostridium, Klebsiella and Methanobrevibacter was significantly higher whereas the abundance of Blautia, Coprococcus, Roseburia was decreased compared toHC (p < .05). The study also showed that 12 biomarkers were capable of distinguishing Schizophrenia subjects from controls using the receiver operating characteristic curve analysis (AUC = 0.837).
	Nguyen et al., 2018 [175] SCZ (n = 25) HC (n = 25)	The genera Anaerococcus (H = 8.32, p = .07) was increased while Haemophilus (H = −11.3, p = .004), Sutterella (H = 8.32, p = .004), Clostridium (H = −15.9, p = .002) were decreased in patients with SCZ compared to HC by using Kruskal-Wallis test.
	Yuan et al. 2018 [154] SCZ (n = 41) HC (n = 41)	Patient with SCZ had lower numbers of faecal Bifidobacterium spp (t = −3.717, p < .001)., E. coli (t = -4.634, p < .001), and Lactobacillus spp. (t = -7.639, p < .001) and higher copy numbers of Clostridium coccoides (t = 6.254, p < .001) using Student T–test. After 24-weeks of risperidone treatment, the was an increase the faecal copy numbers of Bifidobacterium spp. (F(3160) = 7.298, p < .001) and E. coli (F(3160) = 8.280, p < .001) in the patient group. The copy numbers of faecal C. coccoides (F(3160) = 6.364, p < .001) and Lactobacillus (F(3160) = 8.369, p < .001) significantly decreased using ANOVA test.
	Schwarz et al. 2017 [133] FEP (n = 28) HC (n = 16)	In individuals experiencing their first episode of psychosis with increased levels of the Lactobacillus correlated significantly with symptom severity and function (p = .004).
Bipolar Disorder	Coello K, et al.2019 [123] BPD (n = 113) FDR (n = 39) HC (n = 77)	The genus Flavonifractor was found more in BPD patients compared to both healthy FDR and HC (OR of 2.9 (95%CI: 1.6–5.2, p = 5.8 × 10^−4, Q = 0.036) by regression analysis.
	Evans et al. 2016 [55] BPD (n = 115) HC (n = 64)	Patients with a history of BPD were shown to have a decreased fractional representation of Faecalibacterium (p < .001) compared to HC using OTU level analysis.
	Rong et al. 2019 [167] MDD (n = 31) BPD(D) (n = 30) HC (n = 30)	Both MDD and BPD showed increased levels of the phyla Firmicutes (p < .01) and Actinobacteria (p < .01) while Bacteriodetes were decreased (p < .01) compared to HC using Wilcoxon Rank Sum test. The Proteobacteria (p = .010) showed significant changes only between the BPD and HC groups. On a genus level Bacteroides, Clostridium, Bifidobacterium, Oscillibacter and Streptococcus were increased (p < .01) in BPD and MDD patients. Only BPD patients showed increased abundance with Escherichia and Klebsiella (p < .01) compared to HC.
	Aizawa et al. 2018 [176] BP (n = 39) HC (n = 58)	Did not find any significant difference in abundance of Lactobacillus or Bifidobacterium between BP patients and HC. A negative correlation between Lactobacillus and sleep scores on the HAM-D (ρ = −.45, p = .01). A negative correlation between serum cortisol levels and Bifidobacterium (ρ = −.39, p = .02) was also found. Limitation of the study is mild Bipolar disorder subjects and the specific species of bacteria related to the disorder was not studied.
	Painold et al. 2018 [126] BP (n = 32) HC (n = 10)	BP patients had more abundance of the Phylum Actinobacteria (LDA  =  4.82, p = .007) and Class Coriobacteria (LDA  =  4.75, p = .010) while HCs had higher abundance of Family Ruminococcaceae (LDA  =  4.59, p = .018) and Genus Faecalibacterium (LDA  =  4.09, p = .039).

AUC: area under the curve; AD: Alzheimer’s dementia; ANOVA: analysis of variance; ANCOM: analysis of composition of microbiome; BPD: bipolar disorder; BPD(D): bipolar disorder with current major depressive episode; CI: confidence interval; DEP: depressed patients; DEP/ANX: depression or anxiety patient; FABP2: fatty acid-binding protein-2; FDR: first degree relatives; FEP: first episode of psychosis; HAM-D: Hamilton Depression Scale; HC: healthy controls; LDA: linear discriminatory analysis; MDD: major depressive disorder; A-MDD: active MDD; R-MDD: responding MDD; MCI: minor cognitive impairment; OR: odds ratio; OTU: operational taxonomical unit; PLS-DA: partial least square discrimination analysis; PTSD: post-traumatic stress disorder; TE: trauma-exposed controls; SCZ: schizophrenia.

Microbial Richness – determines the richness of different species using a measure of OUT present in a sample [177]. This value can be estimated used the abundance-based coverage estimator (ACE) or the Choa1 abundance estimator [178].

Alpha-Diversity – A measure of the microbial diversity in a specific sample and used to evaluate if a particular variable has an effect on the sample’s richness or abundance evenness. Can be expressed as a measure of OTUs, the Shannon index, Faith’s phylogenetic diversity, or Simpsons diversity index [178].

Beta-Diversity – A measurement that compares the shared diversity between samples. Can be measured as the OUT sharing between individuals using Bray–Curtis dissimilarity or Unifrac measurements [178].

Abundance – The quantity of microorganisms in a particular environment. Often measured with the use of 16 sRNA and shotgun metagenomics. Frequently expressed as a substantial difference in the relative abundance between two groups of samples [179].

Table 3. Antimicrobial properties of psychotropic medications on the gut microbiota.

Class	Medication	Type of study	Proposed mechanism of action	Reference
Antidepressant	Amitriptyline	In vitro	Inhibits growth of Staphylococcus spp., Bacillus spp., Vibrio cholerae, Cryptococcus spp. and Candida albicans	Mandal et al. 2010 [180]
		In vivo	Protects mice from Salmonella typhimurium	Mandal et al. 2010 [180]
	Clomipramine	In vitro	Cytotoxic to Leishmania donovani and Leishmania major	Zilberstein and Dwyer 1984 [181]
	Desipramine	In vitro	Antimicrobial effect on Plasmodium falciparum	Basco and Le Bras 1990 [182]
				Salama and Facer 1990 [183]
		In vivo	Antimicrobial effect of Ruminococcus flavefaciens and Adlercreutzia. equolifaciens	Lukić et al. 2019 [148]
	Duloxetine	In vivo	Antimicrobial effect of R. flavefaciens and A. equolifaciens	Lukić et al. 2019 [148]
	Escitalopram	In vitro	Antimicrobial effect on E. coli	Cussotto et al. 2019 [129]
		In vivo	Antimicrobial effect of R. flavefaciens and A. equolifaciens	Lukić et al. 2019 [148]
	Fluoxetine	In vitro	Antimicrobial activity against E. coli and L. rhamnosus	Cussotto et al. 2019 [129]
		In vivo	Antimicrobial effect of R. flavefaciens and A. equolifaciens	Lukić et al. 2019 148
		In vivo	In rats, inhibits the growth of Succinivibrio and Prevotella	Cussotto et al. 2019 [129]
	Imipramine	In vitro	Cytotoxic against L. donovani and Leishmania major	Zilberstein and Dwyer 1984 [181]
		In vitro	Inhibits growth of E. coli, Yersinia enterocolitica, and Giardia lamblia	Csiszar and Molnar 1992 [184]
				Molnar 1988 [146]
				Weinbach et al. 1992 [185]
	Sertraline	In vitro	Antimicrobial activity against E. coli	Bohnert et al. 2011 [144]
		In vitro	Inhibition of S. aureus, E. coli, and P. aeruginosa growth and antibiotic synergy	Ayaz et al. 2015 [145]
	Venlafaxine	In vivo	Antimicrobial effect of R. flavefaciens and A. equolifaciens	Lukić et al. 2019 [148]
Antipsychotics	Aripiprazole	In vivo	Increases abundance of Clostridium, Ruminiclostridium, Intestinibacter, and Eubacterium coprostanoligens	Cussotto et al. 2019 [129]
		Human	Alteration of Lachnospiraceae, Akkermansia, and Sutterella between controls and patients treated with atypical antipsychotics	Flowers et al. 2017 [135]
	Chlorpromazine	In vitro	Inhibits S. aureus and E. coli growth.	Csisizar and Molnar 1992 [184]
				Amaral and Lorin 1991 [186]
				Ordway et al. 2002 [187]
	Olanzapine	In vitro	Inhibits growth of E. coli and Enterococcus faecalis	Morgan et al. 2014 [155]
		In vivo	Alters the microbiota profile in rats over a 3-week treatment	Davey et al. 2013 [188]
			Causes weight gain in mice over 4-week treatment. This is absent in germ-free mice	Morgan et al. 2014 [155]
			If treated with a probiotic (B-GOS) the weight gain caused by olanzapine is attenuated in female rats	Kao et al. 2018 [156]
		Human	Alteration of Lachnospiraceae, Akkermansia, and Sutterella between controls and patients treated with atypical antipsychotics	Flowers et al. 2017 [135]
	Risperidone	Humans	Alteration of Lachnospiraceae, Akkermansia, and Sutterella between controls and patients treated with atypical antipsychotics	Flower et al. 2017 [135]
Anxiolytics	Propranolol	In vitro	Inhibits E. coli growth with mixed evidence of S. aureus growth inhibition	Kruszewska et al. 2004 [149]
				Hadera et al. 2018 [150]
				Jerwood and Cohen 2008 [151]
Mood stabilisers	Lamotrigine	In vitro	Antibacterial activity against the Gram-positive bacteria B. subtilis, S. aureus, and S. faecalis	Qian et al. 2009 [152]
	Lithium	In vivo	After 4 weeks of treatment there is a change in the caecal microbiome in rats	Cussotto et al. 2019 [129]
	Valproate	In vivo	After 4 weeks of treatment there is a change in the caecal microbiome in rats	Cussotto et al. 2019 [129]

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