Comparison of serum microbiome composition in bipolar and major depressive disorders

https://doi.org/10.1016/j.jpsychires.2020.01.004Get rights and content

Highlights

  • There was no difference in serum microbiome diversity between bipolar disorder and major depressive disorder.

  • Prevotella 2 and Ruminococcaceae UCG-002 genera were more prevalent in major depressive disorder.

  • The apoptosis function differed between bipolar disorder, major depressive disorder, and healthy controls.

Abstract

Bipolar disorder and major depressive disorder are debilitating psychiatric conditions which can be difficult to differentiate; however, recent studies have suggested that microbiome composition may be a potential tool in distinguishing between these two disorders. This study aimed to compare the serum microbiome composition of patients with bipolar disorder, major depressive disorder, and healthy controls. Serum samples were collected from 42 subjects with bipolar disorder, 30 with major depressive disorder, and 36 healthy controls. Bacterial DNA was isolated from bacteria-derived extracellular vesicles in the serum and then amplified and quantified with primers specific to the V3–V4 hypervariable region of the 16S rDNA gene. Sequence reads were clustered into operational taxonomic units and classified using the SILVA database. Alpha and beta diversity, individual taxa analysis based on phylum and genus, and functional pathways were compared. There was no statistical difference between alpha or beta diversity in patients with bipolar disorder and major depressive disorder; however, the Prevotella 2 and Ruminococcaceae UCG-002 genera were significantly more prevalent in patients with major depressive disorder than in either those with bipolar disorder or in healthy controls. Functional analysis of pathways revealed that the apoptosis function differed between all three groups. In conclusion, the Prevotella 2 and Ruminococcaceae UCG-002 genera were identified as potential candidates for distinguishing bipolar disorder and major depressive disorder. Further studies with larger sample sizes, longitudinal designs, and control for other various confounders are warranted.

Introduction

Bipolar disorder (BD) and major depressive disorder (MDD) are prevalent and debilitating psychiatric conditions which increase socio-economic burdens (Cloutier et al., 2018; Greenberg et al., 2015) and mortality rates (Reutfors et al., 2018; Staudt Hansen et al., 2019). As clinical manifestations of the depressive phases of these disorders are similar, they are sometimes difficult to differentiate. Indeed, the misdiagnosis rate of BD as MDD is almost 40% (Ghaemi et al., 2000), resulting in the use of antidepressant monotherapy in BD patients which increases the risk of hypomanic/manic states (Fornaro et al., 2018). The importance of making a correct distinction between these disorders cannot be overstated; therefore, considerable effort is being made to find objective biomarkers to help distinguish these disorders.

Recently, efforts to understand the role of the microbiome in human health and diseases have been extended to psychiatric disorders through the notion of the “gut-brain axis.” Increasing evidence shows that gut microbiota can influence brain function via the vagus nerve, short chain fatty acids, and other immune components (Nguyen et al., 2018). Most studies concerning the influence of the microbiome on mood disorders have analyzed the microbiotic differences between BD or MDD patients and healthy controls (HCs), with mixed results regarding overall diversity and differences at the level of individual taxa (Chen et al., 2018; Chung et al., 2019; Coello et al., 2019; Evans et al., 2017; Jiang et al., 2015; Lin et al., 2017; Liu et al., 2016; McIntyre et al., 2019; Naseribafrouei et al., 2014; Nguyen et al., 2018; Painold et al., 2019). Rong et al. (2019) analyzed the fecal microbiome of BD and MDD patients and HCs, and found significant differences in the abundances of eight species between the BD and MDD patients; however, no significant differences were found in abundances among the genera (Rong et al., 2019).

Our current understanding of variations in the blood microbiome and their relationship to mood disorders is limited. Olde Loohuis et al. (2018) compared the whole-blood microbiomes of patients with schizophrenia, BD, and amyotrophic lateral sclerosis with those of HCs, and found that alpha diversity was significantly higher in patients with schizophrenia than in the other groups, but found no significant differences between patients with BD and HCs (Olde Loohuis et al., 2018). To our knowledge, no studies have yet compared the serum microbiome composition of patients with BD and MDD. Thus, we analyzed the differences between the serum microbiomes of patients with BD and MDD compared with those of HCs. Based on previous studies, we hypothesized that overall measures of diversity would be similar among these groups, but that individual microbial taxa would differ significantly between patients with BD and MDD.

Section snippets

Study participants

In total, 72 patients (42 with BD, 30 with MDD) and 36 HCs were enrolled from Seoul National University Hospital and Inje University Haeundae Paik Hospital, respectively, from 2015 to 2018. Ages ranged from 19 to 60 years. The BD and MDD patients were selected from the out-patient psychiatric clinic of Seoul National University Hospital. Diagnoses were made according to the criteria of the Diagnostic and Statistical Manual of Mental Disorders 4th or 5th version (DSM-IV, or DSM-5), and confirmed

Demographic and clinical characteristics

A comparison of the demographic and clinical characteristics of the BD, MDD, and HC groups (Table 1) shows a significant difference in average age between the groups (F = 17.48, p < 0.001); post-hoc analysis revealed that the average ages of the MDD and HC groups were higher than that of the BD group. Symptom severity did not differ between the BD and MDD groups; however, psychiatric medication usage was significantly different between these groups.

Diversity analysis

The observed OTUs, Chao-1 index, inverse

Discussion

This study was the first to compare serum microbiome composition between patients with BD and MDD. No significant differences were found between the overall diversity measures of the two groups; however, there were differences between two bacterial genera and several functional pathways.

As this study was the first of its kind to focus on serum microbiome composition, we compared our results with previous studies that analyzed microbiome compositions of other sites. We found no significant

Role of funding source

This work was supported by the SNUH (Seoul National University Hospital) Research Fund [grant number 04-2017-0340]. The funding source had no involvement in study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication.

CRediT authorship contribution statement

Sang Jin Rhee: Conceptualization, Formal analysis, Writing - original draft. Hyeyoung Kim: Conceptualization, Methodology, Writing - review & editing. Yunna Lee: Conceptualization, Methodology, Writing - review & editing. Hyun Jeong Lee: Conceptualization, Methodology, Writing - review & editing. C. Hyung Keun Park: Conceptualization, Methodology, Writing - review & editing. Jinho Yang: Methodology, Formal analysis, Writing - original draft. Yoon-Keun Kim: Methodology, Formal analysis, Writing

Declaration of competing interest

Yong Min Ahn receives research support from or serves as a speaker for Janssen Korea Ltd., Lundbeck Korea Co., Ltd, and Korea Otsuka Pharmaceutical. The other authors have no conflict of interest to declare.

Acknowledgement

We are grateful to all who participated in the study.

References (55)

  • T.T. Nguyen et al.

    Overview and systematic review of studies of microbiome in schizophrenia and bipolar disorder

    J. Psychiatr. Res.

    (2018)
  • J. Reutfors et al.

    Mortality in treatment-resistant unipolar depression: a register-based cohort study in Sweden

    J. Affect. Disord.

    (2018)
  • H. Rong et al.

    Similarly in depression, nuances of gut microbiota: evidences from a shotgun metagenomics sequencing study on major depressive disorder versus bipolar disorder with current major depressive episode patients

    J. Psychiatr. Res.

    (2019)
  • A.N. Sarangi et al.

    Methods for studying gut microbiota: a primer for physicians

    J. Clin. Exp. Hepatol.

    (2019)
  • L.Y. Wang et al.

    Systemic autoimmune diseases are associated with an increased risk of bipolar disorder: a nationwide population-based cohort study

    J. Affect. Disord.

    (2018)
  • K.P. Asshauer et al.

    Tax4Fun: predicting functional profiles from metagenomic 16S rRNA data

    Bioinformatics

    (2015)
  • N.A. Bokulich et al.

    Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing

    Nat. Methods

    (2013)
  • T.W. Buford et al.

    Composition and richness of the serum microbiome differ by age and link to systemic inflammation

    Geroscience

    (2018)
  • J.G. Caporaso et al.

    QIIME allows analysis of high-throughput community sequencing data

    Nat. Methods

    (2010)
  • J.J. Chen et al.

    Sex differences in gut microbiota in patients with major depressive disorder

    Neuropsychiatric Dis. Treat.

    (2018)
  • E.J. Cho et al.

    Circulating microbiota-based metagenomic signature for detection of hepatocellular carcinoma

    Sci. Rep.

    (2019)
  • B. Dalile et al.

    The role of short-chain fatty acids in microbiota-gut-brain communication

    Nat. Rev. Gastroenterol. Hepatol.

    (2019)
  • S.A. Flowers et al.

    Interaction between atypical antipsychotics and the gut microbiome in a bipolar disease cohort

    Pharmacotherapy

    (2017)
  • M. Fornaro et al.

    Incidence, prevalence and clinical correlates of antidepressant-emergent mania in bipolar depression: a systematic review and meta-analysis

    Bipolar Disord.

    (2018)
  • S.N. Ghaemi et al.

    Diagnosing bipolar disorder and the effect of antidepressants: a naturalistic study

    J. Clin. Psychiatr.

    (2000)
  • P.E. Greenberg et al.

    The economic burden of adults with major depressive disorder in the United States (2005 and 2010)

    J. Clin. Psychiatr.

    (2015)
  • M. Hamilton

    A rating scale for depression

    J. Neurol. Neurosurg. Psychiatry

    (1960)
  • Cited by (23)

    • Microbiome and bipolar disorder

      2022, Biomarkers in Bipolar Disorders
    View all citing articles on Scopus
    1

    Present address: Department of Psychiatry, Inha University Hospital, Incheon, Republic of Korea.

    2

    Present address: Department of Psychiatry, Kosin University Gospel Hospital, Busan, Republic of Korea.

    3

    Present address: Department of Psychiatry, Asan Medical Center, Seoul, Republic of Korea.

    View full text