please see the attached document.
pjurrel
P7.pdf
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http://dx.doi.org/10.2147/NDT.S159322
sex differences in gut microbiota in patients with major depressive disorder
Jian-jun chen1–4
Peng Zheng2,3
Yi-yun liu2,3
Xiao-gang Zhong2,3
hai-yang Wang2,3
Yu-jie guo2,3
Peng Xie2,3
1institute of life sciences, 2Department of Neurology, First affiliated hospital, 3institute of Neuroscience, 4Joint international research laboratory of reproduction and Development, chongqing Medical University, chongqing, china
Objective: Our previous studies found that disturbances in gut microbiota might have a causative role in the onset of major depressive disorder (MDD). The aim of this study was to investigate
whether there were sex differences in gut microbiota in patients with MDD.
Patients and methods: First-episode drug-naïve MDD patients and healthy controls were included. 16S rRNA gene sequences extracted from the fecal samples of the included subjects
were analyzed. Principal-coordinate analysis and partial least squares-discriminant analysis
were used to assess whether there were sex-specific gut microbiota. A random forest algorithm
was used to identify the differential operational taxonomic units. Linear discriminant-analysis
effect size was further used to identify the dominant sex-specific phylotypes responsible for
the differences between MDD patients and healthy controls.
Results: In total, 57 and 74 differential operational taxonomic units responsible for separating female and male MDD patients from their healthy counterparts were identified. Compared with
their healthy counterparts, increased Actinobacteria and decreased Bacteroidetes levels were
found in female and male MDD patients, respectively. The most differentially abundant bacte-
rial taxa in female and male MDD patients belonged to phyla Actinobacteria and Bacteroidia,
respectively. Meanwhile, female and male MDD patients had different dominant phylotypes.
Conclusion: These results demonstrated that there were sex differences in gut microbiota in patients with MDD. The suitability of Actinobacteria and Bacteroidia as the sex-specific
biomarkers for diagnosing MDD should be further explored.
Keywords: major depressive disorder, MDD, gut microbiota, biomarker
Introduction Major depressive disorder (MDD) is a mental disorder characterized by loss of interest
in normally enjoyable activities, low self-esteem, and low energy. This disease imposes
a huge economic burden on the whole society. The pathogenesis of MDD is still
unclear, and there are no objective diagnostic methods or 100%-effective treatment
methods.1,2 Many factors, such as genetics, biochemical or neurophysiological changes,
and psychosocial variables, are associated with MDD.3,4 Recently, many researchers
have attempted to explain its pathogenesis using neuroanatomical abnormalities,
neurotransmission deficiency, and neurotrophic alterations.5 However, none of these
theories has been universally accepted. Therefore, there is an urgent need to identify
novel pathophysiologic mechanisms underlying MDD.
A previous study reported that gut microbiota could influence all aspects of physi-
ology.6 Many diseases have been found to be related to disturbed gut microbiota, such
as obesity and diabetes.7,8 Researchers have also found that gut microbiota had an
influence on brain function and behavior through the microbiota–gut–brain axis.9,10
Our previous study proved that gut microbiota could influence the expression levels of
correspondence: Peng Xie Department of Neurology, First Affiliated hospital, chongqing Medical University, 1 Yixueyuan road, Yuzhong, chongqing 400016, china Tel +86 23 6848 5490 Fax +86 23 6848 5111 email [email protected]
Journal name: Neuropsychiatric Disease and Treatment Article Designation: Original Research Year: 2018 Volume: 14 Running head verso: Chen et al Running head recto: Gut-microbiota sex differences in MDD DOI: 159322
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chen et al
genes in the hippocampi of mice.11 Meanwhile, our previous
metabolomic studies showed an interesting phenomenon
wherein several differential metabolites in MDD patients
were the metabolic byproducts of gut microbiota.12,13 More-
over, clinical studies have reported disturbed gut microbiota
in limited samples of depressed patients.14,15 Based on these
results, we conducted a further study, and found that the
dysbiosis of gut microbiota might be a contributory factor
in the development of MDD.16
Nowadays, the disproportionate prevalence of MDD in
women might be the most consistent finding among studies
on MDD. In our previous study, compared to healthy con-
trols (HCs), the relative abundance of Bacteroidetes and
Actinobacteria were found to be significantly changed in
patients with MDD.16 However, possible sex differences
in gut microbiota were not taken into consideration. Actu-
ally, our previous metabolomic study found that there were
divergent urinary metabolic phenotypes between males
and females with MDD.17 Yurkovetskiy et al reported that
hormonal regulation of microbe-controlling mechanisms
could result in differences in microbial composition between
males and females.18 Moreover, a recently published study
reported that there were sex-specific transcriptional signa-
tures in human depression.19 Therefore, we hypothesized
that there were sex differences in gut microbiota in patients
with MDD, and conducted this study to identify sex-specific
gut microbiota.
Patients and methods subject recruitment The protocol of this study was reviewed and approved by
the ethical committee of Chongqing Medical University
(Chongqing, China). The methods were carried out in
accordance with approved guidelines and regulations. The
17-item Hamilton Depression Rating Scale (HDRS-17)
was used to assess depression severity.20 Two experienced
psychiatrists studying and treating depression for several
years systematically used the HDRS-17 to diagnose each
participant. MDD patients who met the following criteria
were included: $18 years old, first-episode drug-naïve,
and without obesity, diabetes, substance abuse, preexisting
physical diseases, or other mental disorders. HCs did not
have any previous lifetime history of Diagnostic and Statis-
tical Manual of Mental Disorders IV axis I/II neurological
diseases or systemic medical illness. MDD patients receiving
nonpharmacologic treatments were also excluded. Subjects
using antibiotics or probiotics were excluded. Pregnant,
nursing, or currently menstruating candidates were excluded.
All subjects recruited provided written informed consent.
MDD patients and HCs were recruited from the psychiatric
center and medical examination center, respectively.
16s rrNa gene sequencing Fecal samples were collected and stored at -80°C prior to analysis. The standard PowerSoil kit protocol was used to
extract bacterial genomic DNA. Briefly, the frozen samples
were thawed on ice and then pulverized with a pestle and mor-
tar in liquid nitrogen, we added MoBio lysis buffer to these
fecal samples and then mixed them, and after centrifuging,
we placed the obtained supernatant into MoBio garnet-bead
tubes containing MoBio buffer. Extracted V3–V5 regions of
the 16S rRNA gene from these fecal samples were ampli-
fied by polymerase chain reaction with bar-coded universal
primers containing linker sequences for pyrosequencing.21
The 454 sequencing system (Hoffman-La Roche, Basel,
Switzerland) was used.
16s rrNa gene-sequencing analysis In order to obtain unique reads, Mothur 1.31.2 was
used to quality-filter the raw sequences obtained from
454 sequencing.22 Sequences meeting any one of the follow-
ing criteria were excluded: ,200 bp or .1,000 bp, contained
any bar-code mismatches, primer mismatches, or ambiguous
bases, and contained homopolymer runs exceeding six bases.
Finally, the remaining sequences were assigned to operational
taxonomic units (OTUs) and then taxonomically classified
using RDP reference database.23 To calculate the relative
abundance of gut microbiota at different levels, summaries
of taxonomic distributions of OTUs were constructed using
these taxonomies. Four parameters (observed species, phylo-
genetic diversity, Shannon index, Simpson index) were used
to calculate α-diversity.24 β-Diversity was reported accord- ing to principal-coordinate analysis (PCoA).25 Meanwhile,
both PCoA and partial least squares-discriminant analysis
(PLS-DA) were used to find out whether MDD patients
could be separated from HCs. A random forest algorithm
was used to identify the differential OTUs responsible for
sample differentiation. Cytoscape 3.2.1 software was used
to analyze the potential relationship between demographic
data and differential OTUs. Finally, the linear discriminant-
analysis effect size (LEfSe) was further used to identify the
dominant sex-specific phylotypes responsible for differences
between MDD patients and HCs.26
Results Demographic data A total of 24 first-episode drug-naïve female MDD patients
and 24 demographically matched female HCs were recruited.
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gut-microbiota sex differences in MDD
The average ages of these MDD patients and HCs were
41.5±11.53 and 43.95±12.11 years (P=0.475), respec- tively. These MDD patients (22.01±2.17 kg/m2) and HCs (22.63±2.43 kg/m2) had similar average body-mass index (BMI; P=0.356). The average HDRS scores of these MDD patients were 23.04±4.93. Meanwhile, 20 first-episode drug-naïve male MDD patients and 20 demographically
matched male HCs were recruited. The average ages
of these MDD patients and HCs were 40.35±11.05 and 42.80±15.13 years (P=0.562), respectively. These MDD patients (22.22±2.18 kg/m2) and HCs (22.50±2.25 kg/m2) had similar average BMI (P=0.694). The average HDRS scores of these MDD patients were 23.9±3.68. Three female and two male MDD patients had coexisting
anxiety disorders.
Disturbed gut microbiota The majority of the obtained OTUs belonged to four phyla
(female vs male): Firmicutes (73% vs 75.2%), Bacteroidetes
(10% vs 9.7%), Actinobacteria (6.5% vs 6.8%), and Pro-
teobacteria (4.8% vs 5.3%). The results of within-sample
(α) phylogenetic diversity analysis showed no significant differences between MDD patients and HCs. The results of
PCoA showed that gut microbial community composition
was significantly different between female MDD patients
and HCs (Figure 1A). The PLS-DA model showed similar
results (Figure 1B). Meanwhile, the PCoA and PLS-DA
models also showed significant differences in gut microbial
community composition between male MDD patients and
HCs (Figure 2).
Differential gut microbiota A random forest classifier was used to identify the key dis-
criminatory OTUs responsible for separating MDD patients
from HCs. In total, 57 OTUs whose relative abundance could
reliably distinguish female MDD patients from female HCs
were identified. Of these differential OTUs, the 29 increased
OTUs in female MDD patients were mainly assigned to
the families of Coriobacteriaceae, Lachnospiraceae, and
Ruminococcaceae, and the 28 decreased OTUs were mainly
assigned to the families of Lachnospiraceae and Ruminococ-
caceae (Figure 3). These differential OTUs were mainly
assigned to the phyla Firmicutes (45 of 57, 78.9%), Acti-
nobacteria (six of 57, 10.5%), and Bacteroidetes (three of
57, 5.3%). Meanwhile, 74 OTUs whose relative abundance
could reliably distinguish male MDD patients from HCs
were identified. Of these differential OTUs, the 21 increased
OTUs in male MDD patients were mainly assigned to the
families of Lachnospiraceae and Erysipelotrichaceae, and the
decreased 53 OTUs were mainly assigned to the families of
Lachnospiraceae and Ruminococcaceae (Figure 4). The phyla
these were mainly assigned to were Firmicutes (62 of 74,
83.8%), Actinobacteria (three of 74, 4%), and Bacteroidetes
(six of 74, 8.1%). Compared with female HCs, the relative
abundance of Actinobacteria was increased in female MDD
patients. Compared with male HCs, the relative abundance
of Bacteroidetes was decreased in male MDD patients.
Dominant phylotypes Dominant phylotypes responsible for the differences between
MDD patients and HCs were identified by the metagenomic
Figure 1 Obvious differences in gut microbial composition between female MDD patients and hcs. Notes: (A) Three-dimensional principal-coordinate analysis; (B) partial least squares-discriminant analysis. Abbreviations: MDD, major depressive disorder; hcs, healthy controls.
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Figure 2 Obvious differences in gut microbial composition between male MDD patients and hcs. Notes: (A) Three-dimensional principal-coordinate analysis; (B) partial least squares-discriminant analysis. Abbreviations: MDD, major depressive disorder; hcs, healthy controls.
Figure 3 heat map of differential operational taxonomic unit abundance between female MDD patients and hcs. Notes: assignment of each operational taxonomic unit provided at right. green and red indicate increase and decrease, respectively. Abbreviations: MDD, major depressive disorder; hcs, healthy controls.
LEfSe approach. LEfSe is a new method for metagenomic
biomarker discovery by way of class comparison. In total, 22
bacterial clades with statistically significant and biologically
consistent differences in female MDD patients were identi-
fied (Figure 5A). The most differentially abundant bacterial
taxa in female MDD patients belonged to Actinobacteria.
At the genus level, Actinomyces, Bifidobacterium, Asacchar-
obacter, Atopobium, Eggerthella, Gordonibacter, Olsenella,
Eubacterium, Anaerostipes, Blautia, Roseburia, Faecali-
bacterium, and Desulfovibrio, which were most abundant
in female MDD patients, and Howardella, Sutterella, and
Pyramidobacter, which were most abundant in female HCs,
were the key phylotypes that contributed to the different
gut microbiota between female MDD patients and HCs
(Figure 5B).
Meanwhile, six bacterial clades with statistically significant
and biologically consistent differences in male MDD patients
were identified (Figure 6A). The most differentially abundant
bacterial taxa in male MDD patients belonged to Bacteroidia
(Bacteroidetes). At the genus level, Bacteroides, Erysip-
elotrichaceae incertae sedis, Veillonella, and Atopobium,
which were most abundant in male MDD patients, and
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gut-microbiota sex differences in MDD
Anaerovorax, Gordonibacter, and Pyramidobacter, which
were most abundant in male HCs, were the key phylotypes
that contributed to the different gut microbiota between male
MDD patients and HCs (Figure 6B).
correlation analysis CoNet 1.1 (Cytoscape application) was used to evaluate
correlations among the demographic data and relative
abundance of bacterial genera (Figure 7). For female MDD
patients, six genera (Asaccharobacter, Clostridium XIVa,
Erysipelotrichaceae incertae sedis, Streptococcus, Faeca-
libacterium, and Lachnospira incertae sedis) were nega-
tively correlated with age, three genera (Clostridium XIVa,
Erysipelotrichaceae incertae sedis, and Streptococcus)
were negatively correlated with HDRS score, and one
genus (Streptococcus) was negatively correlated with BMI.
For male MDD patients, one genus (Erysipelotrichaceae
incertae sedis) was negatively correlated with age, two
genera (Veillonella and Collinsella) were negatively and
positively, respectively, correlated with HDRS score, and
Figure 4 heat map of differential operational taxonomic unit abundance between male MDD patients and hcs. Notes: assignment of each operational taxonomic unit provided at right. green and red indicate increase and decrease, respectively. Abbreviations: MDD, major depressive disorder; hcs, healthy controls.
Figure 5 Taxonomic differences in gut microbiota in female subjects. Notes: (A) Bacterial clades (25) with statistically significant and biologically consistent differences in female MDD patients and HCs (LDA score .2); (B) MDD-enriched taxa indicated by positive lDa scores (green), and hc-enriched taxa indicated by negative scores (red). Abbreviations: MDD, major depressive disorder; hcs, healthy controls; lDa, linear discriminant analysis.
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two genera (Dorea and Lachnospira incertae sedis) were
positively correlated with BMI. These results showed that
only three key phylotypes (Erysipelotrichaceae incertae sedis,
Asaccharobacter, and Faecalibacterium) were negatively
correlated with age and one key phylotype (Veillonella) was
negatively correlated with HDRS, while other key phylotypes
showed no correlation with demographic data.
Discussion In total, 57 female-specific and 74 male-specific differential
OTUs were identified. Among these OTUs, only 18 differential
OTUs (mainly assigned to the phyla Firmicutes, 14 of 18,
77.8%) were present in both female and male MDD patients.
The relative abundance of Actinobacteria and Bacteroidetes
was increased and decreased in female and male MDD
patients compared to their healthy counterparts, respectively.
Moreover, the most differentially abundant bacterial taxa
belonged to Actinobacteria in female MDD patients and
Bacteroidia (phyla Bacteroidetes) in male MDD patients.
The dominant phylotypes in female and male MDD patients
were also different. These results demonstrated that there
were sex differences in gut microbiota in patients with MDD,
Figure 7 associations among demographic data (age, BMi, and hDrs) and gut microbiota. Notes: (A) Female and (B) male MDD patients. red lines indicate positive relationships, green lines negative relationship, and circles: red, demographic data; green, Asaccharobacter; blue, Clostridium XiVa; orange, erysipelotrichaceae incertae sedis; dark orchid, Faecalibacterium; yellow, lachnospiraceae incertae sedis; deep sky blue, Streptococcus; crimson, Collinsella; light green, Dorea; pink, Veillonella; olive, others. Abbreviations: BMi, body-mass index; hDrs, hamilton Depression rating scale; MDD, major depressive disorder.
Figure 6 Taxonomic differences in gut microbiota in male subjects. Notes: (A) Twelve bacterial clades with statistically significant and biologically consistent differences in male MDD patients and HCs (LDA score .2); (B) MDD-enriched taxa indicated by positive lDa scores (green), and hc-enriched taxa indicated by negative scores (red). Abbreviations: MDD, major depressive disorder; hcs, healthy controls; lDa, linear discriminant analysis.
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gut-microbiota sex differences in MDD
and the suitability of Actinobacteria and Bacteroidia as the
sex-specific biomarkers for diagnosing MDD should be
further evaluated.
Our previous study found that the relative abundance of
Bacteroidetes and Actinobacteria was significantly decreased
and increased, respectively, in MDD patients.16 The purpose of
this previous study was to investigate whether the dysbiosis
of the gut microbiome played a causal role in the development
of depressive-like behaviors. Therefore, sex-based differ-
ences were not taken into consideration. However, sex-
based differences are prominent in affective disorders.27–29
Our previous metabolomic studies also found sex-specific
differential metabolites in MDD and bipolar disorder.17,30
Therefore, when separately analyzing the differential gut
microbiota in female and male MDD patients, we found that
the Bacteroidetes level was only significantly decreased in
male MDD patients and the Actinobacteria level only signifi-
cantly increased in female MDD patients. Moreover, in order
to rule out the potential influence of antidepressants on gut
microbiota, only drug-naïve MDD patients were recruited,
which might make our conclusion more robust in identifying
sex-specific gut microbiota.
A previous study reported a general underrepresentation
of Bacteroidetes related with depression.14 However, Jiang
et al found that Bacteroidetes levels were increased in MDD
patients.15 In this study, decreased Bacteroidetes levels were
found in male MDD patients. Meanwhile, Jiang et al also
reported the decreased phyla Firmicutes level and increased
phyla Actinobacteria level in MDD patients. However our
results showed that increased Actinobacteria levels were
only found in female MDD patients, and the overall rela-
tive abundance of Firmicutes was not significantly changed
in female or male MDD patients. This disparity might be
caused by the sex factor. Additionally, the differences in
demographic and clinical characteristics of the recruited
MDD patients, sample sizes, and/or statistical methods used
to identify MDD-associated gut microbiota might also have
a role in this disparity. However, these results consistently
showed that MDD was linked to distinct alterations in gut
microbial compositions.
In clinical practice, depression and metabolic-disease
comorbidity, such as diabetes and obesity, is common.31
Previous studies have shown that low Bacteroidetes levels
were associated with obesity.32,33 Stunkard et al reported a link
between depression and obesity through low-grade inflam-
mation.34 Meanwhile, Troseid et al established a correlation
between low-grade inflammation and bacteria.35 Therefore,
in order to rule out the potential influence of obesity and
diabetes, we excluded subjects with either. Finally, the
difference in BMI between MDD patients and HCs was
almost negligible. Moreover, the correlation analysis also
showed that there was no correlation between any key phy-
lotypes and BMI. It is unlikely that obesity or diabetes could
be a confounding factor in this study.
Although no significant differences in the overall abun-
dance of Firmicutes between HCs and MDD patients were
identified in this study, some Firmicutes OTUs in both female
and male MDD patients were increased, while others were
decreased. Therefore, the disturbed Firmicutes could still be a
hallmark in MDD.16 Moreover, the correlation analysis found
that the relative abundance of seven genera (Clostridium XIVa,
Erysipelotrichaceae incertae sedis, Streptococcus, Dorea,
Faecalibacterium, Lachnospira incertae sedis, and
Veillonella) belonging to Firmicutes showed correlations
with age, HDRS score, and BMI. A previous study reported
that there was a negative relationship between the sever-
ity of depressive symptoms and the relative abundance
of Faecalibacterium,15 but in this study only the negative
relationship between the severity of depressive symptoms
and the relative abundance of four other genera (Clostridium
XIVa, Streptococcus, Erysipelotrichaceae incertae sedis, and
Veillonella) was identified. These different results might also
be caused by the sex factor. In addition, a positive relation-
ship between the severity of depressive symptoms and the
relative abundance of Collinsella in male MDD patients
was found here. Schnorr and Bachner reported a reduction
in Actinobacteria levels after intervention, mainly from the
loss of Collinsella.36 As such, Collinsella might also be
a useful index for the clinical management and treatment
of MDD.
The brain can alter gut function, and is widely acknowl-
edged. However, it is less readily accepted that signals from
the gut can influence brain function. Actually, gut microbiota
could regulate the size and composition of bile-acid pool
size, and in turn be an important regulator of the blood–
brain barrier and hypothalamic–pituitary–adrenal axis.37
Meanwhile, metabolites from the gut microbiota have a
significant effect on regulating the gut–brain axis and host
immunity.38 Gut microbiota can also regulate brain func-
tion by influencing tryptophan metabolism39 and influence
the development and activity of brain tissue by regulating
microglia homoeostasis.40 In addition, Sobko et al found
that Lactobacillus could convert nitrate to nitric oxide,
which is a potent regulator of the immune and nervous
systems.41 Previous studies have reported that L. rhamnosus
and L. acidophilus might have an analgesic action on the
host by inhibiting the spinal neuron cellular memory of the
distension.42,43
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Limitations Limitations should be noticed here. First, the number of
recruited samples was relatively small, and the results of
this exploratory research need future studies to verify and
support them. Second, an animal experiment was not per-
formed to determine whether Actinobacteria or Bacteroi-
detes could be potential targets for MDD treatment. Third,
a previous study reported that dietary habits could influence
gut microbiota,44 but the relationship between dietary intake
and gut microbial compositions could not be analyzed here,
because of missing detailed dietary information. However,
our findings were not likely to be significantly influenced
by this potential confounding factor, because of the similar
lifestyles and dietary habits of the recruited samples from
Chongqing. Fourth, all recruited subjects were from the same
place, and thus ethnic biases and site-specificity in microbial
phenotypes could not be ruled out. Fifth, we did not measure
estrogen levels in female patients, but Baker et al reported
that gut microbiota could regulate estrogen levels through
secretion of β-glucuronidase.45 Future studies should explore the potential relationship between estrogen levels and gut
microbiota. Finally, we did not analyze depressive episode
duration, although previous a study found that there was
evidence for the interplay between immune and endocrine
systems in drug-naïve MDD patients with short-illness-
duration first affective episodes.46
Conclusion This study firstly determined that there were sex differences
in gut microbiota in patients with MDD and identified gender-
specific gut microbiota. The most differentially abundant
bacterial taxa in female and male MDD patients belonged to
Actinobacteria and Bacteroidia, respectively. These findings
could provide new insights for uncovering the pathogenesis
of MDD and studying potential gut-mediated therapies for
MDD. However, due to the risk of overseeing effects in small
cohorts, these findings must be verified and supported in the
larger cohorts. Meanwhile, future studies are warranted to
evaluate the suitability of Actinobacteria and Bacteroidia as
sex-specific biomarkers for diagnosing MDD.
Acknowledgments This work was supported by the Natural Science Founda-
tion Project of China (81701360, 81601208, 81771490),
Chongqing Science and Technology Commission (cstc2017j-
cyjA0207, cstc2014kjrc-qnrc10004), Science and Technol-
ogy Research Program of Chongqing Municipal Education
Commission (grant KJ1702037), Special Project on Natural
Chronic Noninfectious Diseases (2016YFC1307200),
National Key Research and Development Program of China
(2017YFA0505700), and National Basic Research Program
of China (973 Program, grant 2009CB918300).
Disclosure The authors report no conflicts of interest in this work.
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