Characteristics of the gut microbiota in bipolar depressive disorder patients with distinct weight

Abstract Background Preliminary studies have indicated metabolic dysfunction and gut dysbiosis in patients with bipolar disorder (BD). In this study, we aimed to clarify the impact of the gut microbial composition and function on metabolic dysfunction in BD patients with an acute depressive episode. Methods Fresh fecal samples were provided from 58 patients with BD depression, including 29 with normal weight (NW) and 29 with overweight/obesity (OW), and 31 healthy controls (HCs). The hypervariable region of 16 S rRNA gene (V3‐V4) sequencing was performed using IonS5TMXL platform to evaluate the bacterial communities. Differences of microbial community and correlation to clinical parameters across different groups were analyzed. Results Compared to NW and HCs, the OW group showed a decreased tendency in alpha diversity index. Beta diversity was markedly different among these groups (PERMANOVA: R 2 = 0.034, p = 0.01) and was higher in patients versus HCs. A total number of 24 taxa displayed significantly different abundance among OW, NW, and HCs. At the family level, the abundance of three taxa was remarkably increased in NW, one in OW, and one in HCs. At the genus level, five taxa were enriched in OW, eight in NW, and two in HCs. The relative abundance of the genera Megamonas was positively associated with BMI, while Eggerthella was negatively correlated with BMI. Functional prediction analysis revealed the metabolism of cofactors and vitamins and amino acid were highly enriched in OW compared to HCs. In addition, microbial functions involved in “lipid metabolism” were depleted while the “fructose and mannose metabolism” was enriched in OW compared to NW group. Conclusions Specific bacterial taxa involved in pathways regulating the lipid, energy, and amino acid metabolisms may underlie the weight concerns in depressed BD patients. Potential targeting gut microbial therapy is provided for overweight/obesity patients with BD, which still need further studies in the future.


| INTRODUC TI ON
Bipolar disorder (BD) is a severe, chronic, and recurrent mental disorder that concerns more than 1% of the worldwide population. 1 BD typically manifests as alternative episodes of (hypo) mania and depression and intermittent remission. 2 Onset of individuals with BD usually occurs around the adolescence, and in recent years, BD has emerged as one of the leading causes of disability and mortality worldwide, which is closely related with high comorbidity with cardiovascular and other metabolic diseases. 3,4 Overweight and obesity are well-known risk factors for cardiovascular diseases. Individuals with BD are at a higher risk for developing obesity or overweight, even in drug-naïve patients. 5 Compared to the general population, about 70% of individuals with BD were troubled with obesity or overweight. 6 Compared to normal-weight patients, mood swings in obese BD patients were more frequent, with a shortened interval of euthymia and poorer response to the medications. 7,8 The body mass index (BMI) of BD patients was positively correlated with suicide attempts. 7 Even in the euthymic phase, the negative relationship between BMI and the attention and processing speed was observed. 9 These evidences indicated a high prevalence of weight problems in BD patients, which may worsen the illness severity, cognitive functions, and prognosis of patients. However, the mechanisms underlying metabolic disturbances in BD patients are still insufficiently elucidated.
Recently, mounting studies have showed that the commensal gut microbiota played an essential role in modulating human health and diseases. The putative role of the microbial dysbiosis in mediating the pathogenesis of obesity has come to the surface. Changes in the fecal richness of Firmicutes and Bacteroidetes were observed in obese subjects. 10,11 Microbial butyrate producers were more prominent in patients with higher BMI. 12 After receiving obesity-associated microbiota via transplantation, the weight of lean mice was recovered. 13 Prebiotic inulin supplementations can reduce the BMI, suppress the adiposity, and mediate hepatic steatosis. 14 In addition, gut microbiota and its metabolites could directly or indirectly influence the host's feeding behavior via stimulating the neuroendocrine release. 15,16 Existing evidence also showed that the dysbiosis of gut microbiota occurred in BD patients and some microbial biomarkers may be useful for BD diagnosis and treatment predication. [17][18][19] However, the alterations of gut microbiota in BD patients with distinct weight have not been systematically studied up till now. Therefore, we proposed the hypothesis that gut microbiota may be involved in the weight changes in BD patients. The aim of the present study is to thus compare the difference of gut microbiota, decipher its relationship with clinical profiles, and predict the functional pathways of microbial genes in BD patients with differed weight. Rating Scale (HAMD-24) was set as the primary enrollment criteria and (2) drug-naive or free from psychotropics for at least 3 months.

| Study subjects
Healthy volunteers without a family or personal history of psychiatric disorders were recruited through advertisement. Exclusion criteria for all subjects included serious physical comorbidities (e.g., heart failure, liver cirrhosis, hematological diseases, and malignancy), alcohol or substance abuse, acute or chronic infection, autoimmune diseases, pregnancy or breastfeeding women, and taking antibiotic or probiotics/prebiotics supplement within 4 weeks prior to sampling.

| Clinical characteristics
Demographic and clinical profiles, including age, gender, duration of illness, family history, and educational level, were collected through face-to-face interviews. The Montgomery-Åsberg Depression Rating Scale (MADRS) and HAMD-24 were used to functions involved in "lipid metabolism" were depleted while the "fructose and mannose metabolism" was enriched in OW compared to NW group.
Conclusions: Specific bacterial taxa involved in pathways regulating the lipid, energy, and amino acid metabolisms may underlie the weight concerns in depressed BD patients. Potential targeting gut microbial therapy is provided for overweight/obesity patients with BD, which still need further studies in the future.

K E Y W O R D S
16 S rRNA, bipolar disorder, gut microbiota, metabolism, weight assess the severity of depression. The Young Manic Rating Scale (YMRS) was used to evaluate the severity of mania. The Hamilton Anxiety Rating Scale (HAMA) was used to estimate the severity of anxiety. The weight and height of all subjects were measured to calculate the BMI value as dividing weight (kg) by height (m) squared. In our study, the overweight/obese was defined as a BMI value not <24 kg/m 2 and normal weight as BMI from 18.5 to 23.9 kg/m 220

| Fecal samples
Fecal samples from each individual were collected using fecal containers. The collected samples were stored in the refrigerator under −80°C prior to processing.

| Statistical analysis
The IBM SPSS Statistics (Version 21) and R software (version.4.1.0) were used for the statistical analysis. Comparisons for normal continuous variables among these three groups were performed with one-way analysis of variance (ANOVA). Chi-square test was carried out for categorical data. Difference of the non-normal continuous variables was analyzed by using the Kruskal-Wallis test. Correlations between clinical variables and specific bacterial taxa in patients were performed using Spearman's correlation analysis and visualized by "pheatmap package." The ggplot2 package was used to produce plots or violin visualizations. The standard of the statistical significance was set as p values <0.05.

| Clinical characteristics of the recruited subjects
In total, 89 subjects were recruited in this study, including 58 type II BD patients with a current depressive episode and 31 healthy controls (HCs). Subsequently, BD patients were further divided into two groups: the normal body weight (NW) and the BD patients with overweight/obese (OW) according to the aforementioned BMI criterion. Gender, age, and educational level are well matched among these three groups. The general clinical characteristics of OW, NW, and HCs groups are summarized and presented in Table 1. When compared to the HCs group, higher HAMA, HAMD, MADRS, and YMRS scores were presented in OW and NW groups (p<0.05). In OW group, the weight and BMI values were significantly the highest (p<0.05).

| Gut microbial diversity
As shown in Figure 1, the alpha diversity of the OW group was the lowest (Shannon, Simpson, chao 1 and ACE), albeit no statistical difference was observed when compared to the NW or HCs groups.
Based on the Bray-Curtis distance at the OUTs level, the analysis of PCoA presented a marked difference in the OW and NW groups when compared to the HCs group in the first two principal coordinates (PC1, PC2), confirmed by the PERMANOVA test (R 2 = 0.034, p = 0.01) (Figure 2A). This result indicated the intergroup variability of the bacterial community had a clear separation among these groups. Additionally, compared to HCs, the beta diversity was higher in both OW and NW groups ( Figure 2B).

| Differential taxonomic compositions of gut microbiota in OW, NW, and HCs groups
The LEfSe analysis showed a total of 24 bacterial taxa changed in the OW, NW, and HCs groups (the LDA score >2, p < 0.05). Among them, The abundance of the genera Lachnospira and Halomonas was higher in HCs ( Figure 3A,B).

| Associations between gut microbiota and clinical parameters
Correlations between the identified bacterial genera and the BD clinical parameters were evaluated. Results showed that there was an obviously negative relationship between BMI and the abundance of Eggerthella, while Megamonas and Oxalobacter were positively correlated with BMI. In addition, a negative correlation was observed between the severity of depression and the abundance of genera Alcaligenes (Figure 4).

| Functional Prediction Analysis
Based on the OTUs' reference sequence, the PICRUSt was used to predict the functional capacities of the bacterial genes. The heatmap presented the differential genes cluster features at levels 2 and 3 of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, respectively ( Figure 5A,B).
In the level 2 KEGG pathways, the function of microbial gene that involved in the lipid metabolism was significantly enriched in NW group ( Figure 6A). In the level 3, there were to-tally12 KEGG pathways generated among OW, NW, and HCs groups. In details, compared to NW group, the glyceropholipid metabolism was reduced while the pathway of fructose and mannose metabolism and the glycosyltransferases were increased in the OW group ( Figure 6B). Compared to the HCs group, the function of microbial gene that involved in the lipid biosynthesis proteins and energy metabolism was significantly reduced in the OW group while the amino acid metabolism and metabolism of cofactors and vitamins were highly enriched in the OW group TA B L E 1 Demographic characteristics and clinical data in all recruited subjects.

BD (n = 58)
HCs (n = 31)  ( Figure 6C). For the NW group, the carbon fixation in photosynthetic organism, cell motility and secretion and Vitamin B6 metabolism was decreased, while the tetracycline biosynthesis, chloroalkane and chloroalkene degradation were enriched ( Figure 6D).

| DISCUSS ION
This study provided evidence that depressed BD patients with distinct weight displayed different gut microbial communities.
Associations between the identified gut microbiota and clinical Our results showed that the microbial diversity was different among these groups. Microbial richness and evenness, as evaluated by the alpha diversity indexes, had a diminished trend in the OW group, albeit this difference had no significant statistical significance. This fingding was consistent with the study of Martínez-Cuesta et al. 22 However, beta diversity in patients was increased in our study. When fed with a high-fat diet for 12 weeks, the beta diversity of gut microbiota in mice was increased in parallel with the weight. 23 These results indicated that an increased beta diversity may be linked to the weight gain. However, data from literatures regarding the microbial diversity in obese individuals are inconsistent due to various factors, such as age, dietary patterns, physical fitness, and geographical differences.
In this study, the taxonomic signatures of microbiota in BD patients with distinct weight were distinguished from those of HCs. In and provides further clues that the gut microbial dysbiosis existed in overweight/obese patients with BD. Interestingly, the amount of the phyla Firmicutes and Bacteroidetes accounts for over 90% of the distal gut microbiota. 25 An increased Firmicutes to Bacteroidetes (F/B) phylum ratio was related with the obese feature. 26 The phyla Firmicutes produce the short-chain fatty acids (SCFAs) via metabolizing dietary fibers, which can accelerate energy accumulation and lipogenesis following high-carbohydrate diets. 27,28 In addition, the phyla Firmicutes encoded less carbohydrate-degrading enzymes than Bacteroidetes. 29  with Sato et al. 32 Megamonas is able to ferment glucose into acetic and propionic acid, thus serving as a substrate for lipogenesis and cholesterol formation and provide energy for the host. 33 Megamonas spp. also carries bacterial α-amylase, which may cause dyslipidemia through the acetyl-CoA synthesis. 34 Strains of Eggerthella are capable of metabolizing bile acids, which act as signaling molecules to regulate the lipid metabolism. [35][36][37] Therefore, we assumed that these two identified genera may be involved in the disrupted lipid metabolism in depressed BD patients.

F I G U R E 5
The cluster heatmap showed the predicted function pathways of the microbial gene at the level 2 and 3 KEGG database. OW: Patients with overweight/obesity; NW: Patients with normal weight; HCs: Healthy controls.
Lastly, we utilized the PICRUSt analysis to preliminarily explore the difference about microbial metabolic pathways among these samples. Herein, our results showed that microbial functions involved in "lipid metabolism" were depleted while the "fructose and mannose metabolism" was enriched in OW compared to NW group.
Furthermore, the microbial genes associated with "Amino acid metabolism" and "Metabolism of cofactors and vitamins" were enriched in OW patients rather than healthy controls, all of which were consistent with the previous studies. 38,39 Changes in microbial compositions directly affect the production of microbe-derived metabolites, including amino acids, lipids and their byproducts, and some of them can activate the ligands of the G protein-coupled receptor, accelerate the production of peptide YY, inhibit gut motility and energy extraction from food and play crucial roles in metabolic disorders. 40,41 Furthermore, specific bacteria can not only inhibit the lipid synthesis but also increase the amino acid level via enhancing the expression of transcriptional factors. 42 Therefore, we hypothesized that the reduced lipid and increased amino acid metabolism in our study may partly be attributed to the above clues. In addition, previous studies regarded elevations in some amino acid as risk factors for obesity. 43,44 Cofactors and vitamins could provide substance for many physiological processes, including amino acid metabolism. 45 The abundance of pathway related to amino acid and vitamins was both increased in our study and these data indicated that gut microbiota of OW patients may have an enhanced capacity for amino acid metabolism. Certainly, the mechanism of the alterations in predicted metabolic pathways caused by microbiota in BD patients is still in its infancy and needed to be further explored.
This study has some inherent limitations. First, the sample size may be relatively small and the difference of the OTUs among these three group was weak according to the values of PERMANOVA test.
Therefore, further verifications on larger sample sizes are needed.
This work is a cross-sectional study and cannot yield any causality between the gut dysbiosis and obesity. Although the recruited participants lived in the same region, other factors such as diet patterns and physical activities can also confound the final findings.
Therefore, longitudinal studies with well-designed control on mixed factors are required in the future.

| CON CLUS ION
Overall, this study provides support for the dysbiosis of gut microbe and its relationship with the weight changes in depressed BD pa- studies are required to obtain cause-effect mechanism between the microbiota and overweight/obesity in BD patients.

AUTH O R CO NTR I B UTI O N S
PZ was in charge of the analysis of data, interpretation of the results, and writing the manuscript. DZ and JL searched the references, interpreted the results, and revised the manuscript. YF, LW, HH, YP, CX, and ZC collected the samples. XS and SH provided the concept and revised the manuscript. All authors approved the final version of the manuscript.

CO N FLI C T O F I NTE R E S T
All authors declare that there are no conflicts of interest.

DATA AVA I L A B I L I T Y S TAT E M E N T
The data that support the findings of this study are available from the corresponding author upon reasonable request. Due to the patients' privacy and ethical restrictions, the dataset is not publicly available.