Gut microbiome in Schizophrenia: Altered functional pathways related to immune modulation and atherosclerotic risk

Abstract

Emerging evidence has linked the gut microbiome changes to schizophrenia. However, there has been limited research into the functional pathways by which the gut microbiota contributes to the phenotype of persons with chronic schizophrenia. We characterized the composition and functional potential of the gut microbiota in 48 individuals with chronic schizophrenia and 48 matched (sequencing plate, age, sex, BMI, and antibiotic use) non-psychiatric comparison subjects (NCs) using 16S rRNA sequencing. Patients with schizophrenia demonstrated significant beta-diversity differences in microbial composition and predicted genetic functional potential compared to NCs. Alpha-diversity of taxa and functional pathways were not different between groups. Random forests analyses revealed that the microbiome predicts differentiation of patients with schizophrenia from NCs using taxa (75% accuracy) and functional profiles (67% accuracy for KEGG orthologs, 70% for MetaCyc pathways). We utilized a new compositionally-aware method incorporating reference frames to identify differentially abundant microbes and pathways, which revealed that Lachnospiraceae is associated with schizophrenia. Functional pathways related to trimethylamine-N-oxide reductase and Kdo₂-lipid A biosynthesis were altered in schizophrenia. These metabolic pathways were associated with inflammatory cytokines and risk for coronary heart disease in schizophrenia. Findings suggest potential mechanisms by which the microbiota may impact the pathophysiology of the disease through modulation of functional pathways related to immune signaling/response and lipid and glucose regulation to be further investigated in future studies.

Keywords: Accelerated aging; Bacteria; Functional pathways; Gut-brain axis; Inflammation; Microbes; Psychosis; Serious mental illness.

Figure 1.. Beta-diversity of microbial taxa was significantly different between schizophrenia and NC groups.

PCoA plots are a multivariate reduction method to depict beta-diversity distance matrices of microbial taxa between samples. Each point represents an individual subject. (A) Unweighted UniFrac measures the presence or absence of unique branch lengths in a phylogenetic tree, while (B) Bray-Curtis is a non-phylogenetic method that considers relative abundance. Both unweighted UniFrac (A) and Bray-Curtis (B) distance metrics show a high degree of separation between participants with schizophrenia (red) compared to NC participants (blue) along Axis 3.

Figure 2.. Differential rankings of taxa associated with diagnosis.

(A) Qurro visualization displaying the sorted differential rankings of taxa associated with schizophrenia vs. NC groups, as determined by Songbird. Left on the x-axis indicates relative over-expression in NCs, right indicates relative over-expression in schizophrenia. Sequences associated with family Lachnospiraceae are highlighted in blue; the top-20 ranked taxa are highlighted in yellow. (B) The log-ratio of Lachnospiraceae to the top-20 ranked taxa is significantly increased in schizophrenia, compared to NCs (Z = −3.072, p = 0.002).

Figure 3.. Three predicted functional pathways were differentially abundant between schizophrenia and NC groups: trimethylamine-N-oxide (TMAO) reductase, glycerol degradation to 1,3-propanediol, and Kdo₂-lipid A biosynthesis.

(A) The log-ratios of TMAO reductase (TMAOr), relative to the bottom-20 pathways (i.e., pathways most associated with schizophrenia), were significantly lower in schizophrenia, compared to NCs. K07821: Z = −3.80, p < 0.001, q < 0.001; EC 1.7.2.3: Z = −4.19, p < 0.001, q < 0.001. (B) The log-ratio of glycerol degradation to 1,3-propanediol pathway (GlycProp), relative to the top-20 pathways (i.e., most associated with NCs), was significantly increased in schizophrenia, whereas the log-ratio of Kdo₂-lipid A biosynthesis pathway, relative to the bottom-20 pathways, was significantly decreased in schizophrenia group, compared to NCs. GOLPDLCAT-PWY: Z = −4.36, p < 0.001, q < 0.001; KDO-NAGLIPASYN-PWY: Z = −3.33, p = 0.001, q < 0.001 (C) Greater log-ratios of TMAOr/bottom-20 were associated with greater Framingham Risk Scores in schizophrenia, and greater log-ratios of Kdo₂-lipid A/bottom-20 was correlated with decreased levels of IL-10.

Figure 4.. Accuracy of supervised Random Forests classification models.

(A) Microbial classification predicted schizophrenia vs. NCs with 75% accuracy. Area under the ROC curve was 0.82, indicating good classification accuracy. Functional classification predicted diagnosis with (B) 67% accuracy for KEGG orthologs and (C) 70% for MetaCyc pathways. All ROC curves were produced from stratified 5-fold cross-validation results, while the confusion matrices were generated from the best model obtained in cross-validation.