References | Subject type | Investigated actors | Methods | Results |
---|---|---|---|---|
Pyndt Jørgensen et al. [22] | Rats | Cognitive abilities (memory performances) | Sub-chronic PCP model to induce SCZ-like behaviors | SubPCP model impaired NORT |
Increased locomotor sensitivity up to 6Â weeks after washout | ||||
NORT | ||||
16S rRNA gene MiSeq-based high throughput sequencing | ||||
Locomotor activity | Gut microbiota profiles correlated to SCZ-like memory performance | |||
Administration of ampicillin (restoring gut microbiota) abolished the subPCP-induced memory deficit | ||||
Gut microbiota | ||||
Nguyen et al. [30] | Human | α-diversity | Stool sampling | Phylum level |
16S rRNA amplicon extraction protocol |  ↓ Proteobacteria in SCZ vs HC | |||
Illumina primers to target the V4 region of the 16S ribosomal RNA gene | ||||
Genus level | ||||
 ↑Anaerococcus in SCZ | ||||
 ↓Haemophilus, Sutterella, and Clostridium in SCZ | ||||
β-diversity | ||||
Within SCZ | ||||
 Ruminococcaceae correlated with low negative symptoms | ||||
Zheng et al. [85] | Human, mice | Gut microbiota of SCZ and HC | 16S rRNA gene sequencing | ↓ Microbiome α-diversity index in SCZ |
↓ Disturbances of gut microbiota composition | ||||
Veillonellaceae and Lachnospiraceae associated with SCZ severity | ||||
Human-to-mice Gut microbiota transplant | ||||
SCZ-relevant behavioral phenotypes in GF mice | ||||
Whole-genome shotgun sequencing of cecum | GF mice receiving SCZ microbiome | |||
 HPC ↓glutamate and ↑glutamine and GABA | ||||
Non-targeted metabolomics analysis | ||||
SCZ vs HC mice microbiota analysis | ||||
SCZ-relevant behaviors similar to those with GLU hypofunction | ||||
Severance et al. [90] | Human | Plasma biomarkers for general inflammation and gut microbiota derived inflammation: hs-CRP, LBP, sCD14 | 409 SCZ individuals | Multivariate regression models |
 GI and endocrine conditions was additive for LBP, with associations only when both conditions were present compared to when were absent | ||||
Multivariate and univariate regression models | Â hs-CRP strongly associated with primarily endocrine conditions | |||
Univariate comparisons | ||||
 S. cerevisiae IgG levels were elevated only in GI problematic persons | ||||
IgG antibodies to S. Cerevisiae, bovine milk casein, and wheat gluten | ||||
Babulas et al. [91] | Human | Maternal G/R infections prenatal exposure and SCZ relationship in offspring | 7794 offspring reported maternal G/R infections from obstetric records | Exposure to G/R infections during the periconceptional period is associated with increased SCZ risk, with adjustment for maternal race, education, age, and mental illness |
Diagnosed 71 cases of SCZ and SCZ spectrum disorders | ||||
Dunphy-Doherty et al. [92] | Rats | Social isolation/altered gut microbiota correlation | Behavioral testing: OF/NORT, EPM, CFR, restraint | SI rats showed a few signs of anxiety phenotype (↑ locomotion, ↓ defecation, ↓ CFR). No differences in NORT and EPM |
ELISA | No changes in corticosterone after stress | |||
HPC neurogenesis and brain cytokine levels | 16S rRNA gene MiSeq-based high throughput sequencing | ↓ BrdU/NeuN in dentate gyrus | ||
Post-mortem caecal microbiota composition | Cytokine and mTOR analysis | ↓ Il-6 and IL-10 in HPC | ||
Kannan et al. [93] | Human, mice | T. gondii-induced infection in mice and human cohorts | Mice received 2 T. gondii strains, or NaCl (HC) i.p. injections | In mice |
Serum collection from blood tail 20Â weeks post infection | Â T. gondii infection produced sustained, strain-specific, anti-NMDAR immune responses | |||
Enzyme-linked immunosorbent assays | In humans (USA and Germany cohorts) | |||
IgG class antibodies to the NMDAR |  ↑ NMDAR IgG levels in T. gondii-seropositive SCZ vs HC | |||
Serum IgG antibodies (T. gondii, NMDAR subunit) | ||||
Humans: 2 cohorts (USA, Germany) with | ||||
T. gondii and NMDAR antibody seropositivity |   =  NMDAR IgG levels in medicated T. gondii-seropositive SCZ vs HC | |||
 Blood sampling | ||||
 Subject selection with RBANS | ||||
Maes et al. [94] | Human | Plasma IgA/IgM against 5Â g-negative bacteria | Recruitment (80 SCZ, 38 HC) | IgA/IgM values |
 IgA values associated with the SCZ Deficit Phenotype | ||||
SDS screening (40 out of 80 SCZ) | Â No associations between IgM and the 5Â Gram-negative bacteria | |||
IgM MDA and azelaic acid | ||||
Assessments (MINI, PANSS, BPRS) | Low IgM to MDA and azelaic acid in SCZ deficit phenotype | |||
Immunoassays for | ||||
 IgA and IgM against 5 g-negative bacteria | ||||
SCZ deficit phenotype | Â IgM-mediated autoimmune responses directed against MDA and azelaic acid | |||
Xu et al. [95] | Human | GMEs | Recruitment (84 SCZ  +  HC) | MWAS found 19 different taxonomies in SCZ vs HC; and 12 were increased in SCZ |
Stool sampling and analysis | ||||
↑ MD index in SCZ vs HC | ||||
MEs analysis | ||||
↑ MEs diversity in SCZ,  +  correlation with the MD index | ||||
Gut microbiota taxonomies | 16S rRNA gene MiSeq-based high throughput sequencing | |||
↑ GOGAT in the SCZ guts | ||||
MWAS | ||||
ROC analysis showed that MD index, IgA and GOGAT reached AUC 0.86  →  potential gut markers of SCZ | ||||
MD index | ||||
Correlation and regression analysis | ||||
MD analysis | ||||
ROC analysis | ||||
GOGAT | ||||
ELISA | ||||
Shen et al. [96] | Human | SCZ and HC gut microbiota | 16S rRNA gene MiSeq-based high throughput sequencing | Similar α-diversity SCZ vs HC |
ROC analysis | β-diversity altered  →  increased phylum | |||
 Proteobacteria, Fusobacteria, Firmicutes, Bacteroidetes | ||||
α-diversity | ||||
PICRUSt analysis | β-diversity altered  →  decreased phylum | |||
 Mainly Firmicutes (Clostridia, Streptococcus, etc.) | ||||
β-diversity | ||||
Olde Loohuis et al. [97] | Human | Microbial communities composition in the blood | Recruitment (192 with SCZ, ALS, BPD)  +  HC | ↑ Microbial diversity in SCZ vs ALS, BPD, HC |
High-quality unmapped RNA sequencing reads | ||||
↑ Microbial diversity is inversely correlated with estimated abundance of antigenic CD8  +  T cells in HC | ||||
Kanayama et al. [98] | Human | Gut microbiota of a SCZ patient after ECT | Stool sampling before and after ECT | After ECT |
 ↓ Scores in BPRS and BFCRS | ||||
Gut microbiota differences before and after ECT | ||||
Assessments (BPRS, BFCRS) |  ↓ Clostridium | |||
 ↑ Lactobacillus | ||||
ECT (14 sessions) | ||||
 ↑ Bacteroides | ||||
He et al. [99] | Human | Gut microbiota differences | Stool sampling | ↑ Clostridiales, Lactobacillales, and Bacteroidales in UHR vs HR and HC |
MRS scans | ||||
↑ SCFAs | ||||
Recruitment (81 HR SCZ, 19 UHR SCZ, 69 HC) | ↑ ACC choline in UHR vs HR and HC | |||
Choline concentrations in the ACC | ||||
Yuan et al. [100] | Human | Metabolic parameters | Recruitment (41 SCZ, 41 HC) | ↓ Bifidobacterium, E. Coli, and Lactobacillus in SCZ vs HC |
Assessment (PANSS) | ↑ Clostridium | |||
Post 24-weeks risperidone | ||||
 ↑ Body weight, BMI, hs-CRP, SOD, HOMA-IR | ||||
Blood and stool sampling | ||||
 ↑ Bifidobacterium and E. Coli | ||||
 ↓ Clostridium and Lactobacillus | ||||
Only changes in Bifidobacterium correlated with changes in weight and BMI | ||||
Standard enzymatic methods  +  electro-chemiluminescence immunoassay | ||||
Automatic biochemical analyzer | ||||
Particle-enhanced assay  +  chemical colorimetric assay | ||||
QIAamp fast DNA stool mini kit | ||||
SOD | qRT-PCR | |||
hs-CRP | ||||
Gut microbiota | ||||
Metabolic/microbiota changes relationship | ||||
24-weeks risperidone treatment | ||||
Schwarz et al. [101] | Human | Fecal microbiota | Assessment (extended BPRS, SANS, GAF, food habits, physical activity) | Similar α-diversity SCZ vs HC |
Difference in β-diversity | ||||
 ↑ and ↓ different strains of Phyla (Proteobacteria, Fusobacteria, Firmicutes, Bacteroidetes) | ||||
Stool sampling | In active SCZ patients: | |||
 ↑ Lactobacillaceae | ||||
 ↓ Veillonellaceae | ||||
SCZ-first episode, HC | qRT-PCR | |||
Okubo et al. [102] | Human | B. breve A-1 effects on SCZ-anxiety/depression, and the immune system | 4-weeks B. breve A-1 admin | ↑ HADS and PANSS scores after B. Breve A1 |
Assessment (HADS, PANSS) | ||||
↑ Relative abundance of gut Parabacteroides after in B. breve A1 | ||||
Blood test findings | ||||
Fecal microbiota composition | ||||
Flowers et al. [103] | Human | AAP treatment | Starch tolerability assessment | =  overall microbiota composition at baseline between AAP vs non-AAP |
Stool sampling | ||||
↑ Alistipes in non-AAP | ||||
AAP-microbiome varied with resistant starch admin | ||||
↑ Actinobacteria phylum in AAP-treated | ||||
PowerMag soil DNA isolation kit | ||||
16S rRNA gene MiSeq-based high throughput sequencing | ||||
6Â months prebiotics (resistant starch) | Illumina expression array | |||
Recruitment (37 SCZ, BPD) | ||||
Ghaderi et al. [104] | Human | Effects of vitamin D/probiotic combination on metabolic and clinical SCZ symptoms | Assessment (PANSS, BPRS) | Vitamin D |
Vitamin D3/probiotic every 2 weeks or placebo (12 weeks) |  ↑ PANSS scores | |||
Vitamin D/probiotic co-supplementation | ||||
 ↑ TAC | ||||
 ↓ MDA, hs-CRP | ||||
 ↓ Fasting plasma glucose, QUICKI, HOMA-IR | ||||
Fasting blood sampling | ||||
ELISA | ||||
Antioxidant markers (TAC, GSH, MDA) | ||||
Insulin markers (HOMA-IR, QUICKI) | ||||
Enzymatic kits | ||||
Zhu et al. [105] | Human, mice | FMT from SCZ humans to HC mice | Behavioral testing (OF, RSIT, TCST, NORT, FST, EPM, BM, TST) | SCZ-transplanted mice showed behavioral (cognitive and locomotor) impairments up to 10Â days post FMT |
Cognitive and motor abilities in SCZ-induced mice | Mice stool sampling | |||
↑ Kyn/KynA pathway of Tr degradation in both periphery and brain | ||||
16S rRNA gene MiSeq-based high throughput sequencing | Increased DA in PFC, and 5-HT in HPC | |||
ELISA | ||||
qRT-PCR | ||||
Kyn/KynA pathway of Tr degradation | ||||
Extracellular DA in PFC, 5-HT in HPC |