3.1 Clinical data
In this study, thirty patients with drug-naive first-episode MDD and thirty healthy controls were recruited, respectively. There were no statistically significant differences between patients’ group and controls group in terms of age, height, weight, and tobacco and alcohol consumption (Table 1). Patients group received a standardized treatment and finally got a dose of 20mg/d. The average dose of escitalopram was 16.33 ± 3.46 mg / d. The depressed symptoms of patients improved significantly when the mean time of drugs administration was 34.53±5.18 days and the HAMD score decreased by more than 50%.
Table 1 Demographic characteristics of patients and controls
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Patients (n=30)
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Controls (n=30)
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p-value
|
|
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M±SD
|
|
M±SD
|
|
Age
|
|
44.83±11.00
|
|
43.97±10.57
|
0.757
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Height(m)
|
|
1.68±0.07
|
|
1.70±0.05
|
0.171
|
Weight(Kg)
|
|
67.83±6.86
|
|
69.21±7.14
|
0.447
|
BMI (kg/m2)
|
|
23.99±2.05
|
|
23.83±2.08
|
0.761
|
tobacco(%)*
|
|
46.67%
|
|
30.00%
|
0.288
|
alcohol(%)*
|
|
53.33%
|
|
33.33%
|
0.192
|
*Chi-square test; compared with HCs, P < 0.05; BMI: body mass index
3.2 Sequencing data and Bacterial taxonomic composition
Total 4,790,651 original sequences were obtained from 90 samples. After double-end Reads splicing and filtering, a total of 4,444,748 Clean tags were generated. Each sample generated at least 12,039 Clean tags, and an average value were 49,386 Clean tags. Taxonomic annotation of OTUs based on Silva (bacterial) and UNITE (fungi) taxonomic databases.
At phylum level, the dominated gut microbiota were Bacteroidetes, Firmicutes, Protebacteria and Actinobacteria in three groups. Bacteroidetes and Firmicutes accounted for nearly 90% of the total gut microbiota. At the genus level, the abundance distribution ratio of microbiota was different (p﹤0.05) (Supplementary Table S1). By the calculation, the Firmicutes / Bacteroides ratio of Patients group, Follow-up group and Controls group were 0.64, 0.46, and 0.70, respectively. The ratio in Follow-up group was significantly lower than the other two groups. There were significant differences among the three groups (p﹤0.05) (Figure1).
Between Patients group and Controls group, there were significant differences in the abundance of multiple intestinal flora at the genus level. The relative abundance of Parasutterella, Prevotella_9, Fusobacterium, Prevotella_2, Christensenellaceae_R-7_group, Odoribacter and [Eubacterium] _ruminantium_group in Patients group was significantly lower than that in Controls group. Meanwhile, The relative abundance of Parabacteroides, Lactobacillus, Anaerostipes, Ruminococcaceae_UCG-014 and Dialister was significantly increased in Patients group (p﹤0.05) (Supplementary Table S1).
After escitalopram treatment, the abundance of several gut microbiota, including Christensenellaceae_R-7_group, [Eubacterium] _ruminantium_group and Fusobacterium, in Patients group was lower than that in Controls group and significantly increased in Follow-up group (p﹤0.05). The abundance of gut microbiota Lactobacillus in Patients group was higher than that in Controls group and significantly decreased in the Follow-up group (p﹤0.05). The main change of gut microbiota abundance in Follow-up group was Bacteroides (Supplementary Table S2).
In addition, there were also several differences in the gut microbiota between Follow-up group and Controls group. In Follow-up group, the relative abundance of Parabacteroides, Prevotellaceae, Ruminiclostridium_6, Flavonifractor were significantly increased (p﹤0.05), while that of Prevotella_2, Lachnospira, Collinsella, and Clostridium_sensu_stricto_1 were significantly decreased (p﹤0.05). Moreover, the abundance of Faecalibacterium and Lachnoclostridium in Follow-up group and Patients group was significantly lower than that in Controls group (p﹤0.05) (Supplementary Table S2).
3.3 Diversity analysis
Alpha diversity mainly reflected the richness and diversity of the species in samples. As shown in Figure 3, the Chaos1, Ace, and Shannon indices of Patients group were significantly higher than those of Follow-up group and Controls group, and the Simpson index was significantly lower in Patients group than others. This showed that the number and the diversity of gut microbiota in Patients group were significantly higher than those of Follow-up group and Controls group, and there were statistically differences. Four indices value of Follow-up group was between the values of other two groups, which was significantly different from that of Patients group but not statistically different from that of Controls group. This meant that the Alpha diversity of gut microbiota in patients returned to the normal level. The statistics of Alpha diversity index values of each groups were showed in Table 2.
Table 2 Richness and diversity index values of patients, follow-up and controls
|
Patients
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Follow-up
|
Controls
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ACE
|
254.88±2.30
|
187.39±11.09
|
173.43±3.80
|
Chao1
|
257.38±2.63
|
188.93±11.07
|
172.69±4.46
|
Shannon
|
3.57±0.07
|
3.17±0.11
|
2.99±0.09
|
Simpson
|
0.09±0.01
|
0.12±0.01
|
0.13±0.01
|
Mothur (version v.1.30) software was used to calculate the Alpha diversity index for samples. The larger of the index values of Ace and Chao1showed the greater number of species in the samples. The larger of the Shannon index value and the smaller of the Simpson index value showed more species categories of samples.
Beta diversity was used to compare the similarity of species diversity among different groups. The binary jaccard algorithm was used to calculate β diversity, and there were statistical differences among three groups (R = 0.273, p = 0.001) (Figure 4). The gut microbiota of Patients group was significantly different from Controls group, and the gut microbiota within Patients group was more similar.
In addition, the gut microbiota profiles of some patients treated with escitalopram were more similar to those of the control group, but the others’ profiles remained closer to those of patients. The other analysis methods employed in this study also produced similar results. The unweighted paired average method (UPGMA) was used in the R language tool to perform hierarchical clustering of each groups. It found that the gut microbiota of Patients group was significantly different from that of Controls group, and the gut microbiota of Follow-up group was more like that of Controls group (Supplementary Figure S2).
Spearman correlation coefficient between samples was calculated to draw the heatmap. The closer of the calculated Spearman correlation coefficient was to 1, the redder of the color was in the heat map, thus indicating the stronger correlation between two samples. As shown in Figure 4, the follow-up group could be divided into two subgroups. The gut microbiota profiles of parts of treated patients remained the similar with those of Patients group, while others’ profiles were more like those of Controls group. This result suggested that the gut microbiota of parts of patients returned to the normal state during the remission of depression, which might be corelated with the improvement of the disease. We used LEfSe for the quantitative analysis of biomarkers with in two subgroups (LDA>4). We found that several microorganisms could be selected as biomarkers in the two subgroups. Gut microbiota of follow-up group 2, that the subgroup was associated with Patients group, was differently enriched with p_Bacteroidetes, o_Bacteroidales, c_Bacteroidia, g_Prevotella_9, etc. While gut microbiota of follow-up group 1, that the subgroup was associated with Controls group, was differently enriched with p_Firmicutes, p_Actinobacteria, f_Lachnospiraceae, f_Bifidobacteriaceae, o_Bifidobacteriales, c_Actinobacteria, g_Bifidobacterium, etc (Supplementary Figure S3).