Demographic and clinical characterizations of patients
Demographic information and clinical characteristics of 69 COVID-19 patients were shown in Table 1 and laboratory test indices between two groups were shown in Table 2. The median age of patients was 57 years (IQR:49.5-70.5), the median of length of hospitalization was 12 days (IQR:6.5-17.0) and 14 (34.1%) were men in the mild group. In the mild group, 73.2% of hospitalized patients had at least one underlying disease, and 4.9% were admitted into the ICU. In the severe group, the median age was 71 years (IQR:62.3-82.8) and the median duration of hospitalization was 18.5 days (IQR:10.0-38.6) and 16 were men (57.1%). And there was 92.9% of the patients with underlying diseases and 32.1% of patients were admitted into the ICU.
There were significant differences in age, inpatient days, dyspnea, coexisting disorders, ICUadmission (p<0.05) between the mild group and the severe group (p<0.05). Significant differences were also found in white blood cell count (WBC), neutrophil count (GRA), lymphocyte count (LYMPH), C-reactive protein (CRP), and procalcitonin between two groups (p<0.05). However, there was missing data of procalcitonin in 8 patients and it was not considered in the subsequent analysis.
Table1 Demographic and clinical characteristics between two patient groups
Characteristics
|
Groups
|
P-value*
|
Mild group(n=41)
|
Severe group(n=28)
|
Age[median(IQR)]
|
57.0(49.5-70.5)
|
71.0(62.3-82.8)
|
0.009
|
BMI(kg/m2)
|
25.0(20.3-26.0)
|
24.0(20.5-27.2)
|
0.869
|
Inpatient days
|
12.0(6.5-17.0)
|
18.5(10.0-38.6)
|
0.010
|
Sex,male(%)
|
14(34.1)
|
16(57.1)
|
0.058
|
Symptoms(yes,%)
|
|
|
|
Cough
|
31(75.6)
|
25(89.3)
|
0.154
|
Diarrhea
|
7(17.1)
|
4(14.3)
|
1.000
|
Dyspnea
|
4(9.8)
|
11(39.3)
|
0.003
|
Coexisting disorders(%)
|
|
|
|
Any
|
30(73.2)
|
26(92.9)
|
0.040
|
Hypertension
|
20(48.8)
|
17(60.7)
|
0.329
|
Cardiopathy
|
7(17.1)
|
8(28.6)
|
0.256
|
ICU admission (%)
|
2(4.9)
|
9(32.1)
|
0.007
|
Death during hospitalization(%)
|
2(4.9)
|
3(10.7)
|
0.389
|
Abbreviation: IQR, interquartile range; BMI, body mass index; ICU, intensive care unit.
*P-value<0.05 was considered statistically significant between the mild group and severe group.
Table2 Laboratory test results between two patient groups
|
Groups
|
P-value**
|
Mild group(n=41)
|
Severe group(n=28)
|
IgG[ug/mL,median(IQR)]
|
121.3(58.3-187.6)
|
102.8(55.6-188.1)
|
0.903
|
IgM[ug/mL,median(IQR)]
|
16.3(3.7-33.5)
|
18.0(5.8-39.0)
|
0.961
|
White blood cell count , (×109/L)
|
6.0(5.2-8.0)
|
7.6(6.1-10.6)
|
0.006
|
Neutrophil count, (×109 /L)
|
3.9(3.1-4.7)
|
5.7(4.6-8.7)
|
0.001
|
Lymphocyte count, (×109/L)
|
1.6(1.2-1.9)
|
0.9(0.5-1.8)
|
0.006
|
Hemoglobin(g/L)
|
117.0(100.5-133)
|
111.5(93.0-133.8)
|
0.591
|
C-reactive protein(mg/L)
|
4.0(1.5-9.6)
|
42.4(15.3-72.3)
|
<0.001
|
Procalcitonin (ng/m)
|
0.04(0.03-0.17)*
|
0.15(0.06-0.38)a
|
0.002
|
Abbreviation:IgG: Immunoglobulin G; IgM:Immunoglobulin M
*Partial data missing; ** P-value<0.05 was considered statistically significant between the mild group and severe group.
Microbial richness, abundance and diversity
Sixty-nine specimens including 64 nasopharyngeal swabs and 5 sputum swabs were analyzed by 16s rRNA gene sequencing to study the microbial composition ofrespiratory tract in COVID-19 patients. After merging and filtering the raw reads data, 3957195 high-quality sequence reads were saved for the subsequent analysis. In order to avoid analysis bias caused by different sequence reads of samples, all samples were rarefied to even sequencing depth based on the sample with the lowest sequencing depth. With the increase of sequencing depth, the rarefaction curves increased rapidly and then became flat (Fig. 1), indicating that the sample sequencing data was reasonable and the quality of reads was good with certain depth and representativeness.
According to Simpson diversity index (P=0.0062) and ACE diversity index (P=1.7474e-5), the microbial diversity and the richness of mean community were significantly higher in the mild group than the severe group (Fig.2A, B). PCoA based on Bray-Curtis distances displayed differences in both the mild group and severe group (analysis of similarities, ANOSIM, R=0.143, P<0.003) (Fig. 3).
Different bacterial taxonomic characterizations in the two groups
To investigate alterations in microbiome of the respiratory about COVID-19 patients with different severity, we selected top ten relative abundances at the phylum, class, order, family and genus levels respectively and assessed differences by Mann-Whitney U test in the groups. Then, relative abundances with significant differences at different taxonomic levels were shown in Figure 4 and Table S3. At the phylum level, the relative abundances of Fusobacteria and Bacteroideteswere were lower in the severe group compared with the mild group (Fig. 4A), which was probably due to significant decrease of FusobacteriiaandBacteroidiaat the class level (Fig. 4B). At the class level, except the significant reduction in Bacteroidia and Fusobacteriia, the relative abundances of Clostridia and Negativicutesdecreased in the severe group. At the order level (Fig. 4C), there were seven significant orders including Bacteroidales, Clostridiales, Enterobacteriales, Fusobacteriales, Neisseriales, Pseudomonadales, Selenomonadales, among which the relative abundances of Selenomonadales and Bacteroidales in the mild group were higher than that in the severe group. However, the relative abundance of Pseudomonadales was lower in the mild group than that in the severe group. At the family level(Fig. 4D), the relative abundances of Actinomycetaceae, Micrococcaceae, Prevotellaceae, Streptococcaceae, Veillonellaceaesignificantly decreased in the severe group compared to the mild group. At the genus level,the relative abundances of Actinomyces, Prevotella, Rothia, Streptococcus, Veillonelladecreased in the severe group (Fig. 4E) and this taxonomy bar plot showed the main species composition of each sample (Fig. 5, Table S2), respectively
Biomarkers exploration in the different groups
The random forest model was used to distinguish the different genera of respiratory microbiome between the two groups. The differential genera were ranked by their contribution to the mild and severe disease groups and then the top ten genera were selected as candidate biomarkers (Fig. 6A).
LDA-score>4 by LEfSe analysis was conducted to select candidate biomarkers in the groups. Significant differences were found in twenty-two genera of Acinetobacter, Capnocytophaga, Centipeda, etc., between the mild group and severe group (Fig. 6B). Finally, eighty common genera (Treponema,Lachnoanaerobaculum, Parvimonas, Selenomonas, Alloprevotella, Porphyromonas, GemellaandStreptococcus) were selected to distinguish the two groups. The correlations of enriched genera were analyzed by Spearman’s rank test to evaluate relationships among genera (Fig. 6C). there were positive correlations across different genera with different degrees of COVID-19 severity, except for Acinetobacter.
Relationship between respiratory microbiome composition and clinical characteristics
Spearman’s rank analysis was used to evaluate the relationships of correlation between top 10 genera and clinical characteristics (including age, inpatient days, dyspnea, coexiting diseases and days in the ICU) and indexes (WBC, GRA, LYMPH and CRP) in the mild group and severe group, respectively (Fig. 7, Table S4). According to Figure 7A and 7B, the genera of Actinomyces andPrevotella were negatively correlated with age in the two groups. The genera of Acinetobacter and Streptococcus were positively correlated with dyspnea in the severe group, but these genera were uncorrelated with dyspnea in the mild group. Moreover, inpatient days, ICU admission, GRA and LYMPH were correlated with different genera in the two groups. In addition, there were a positive correlation between Klebsiella and WBC in two groups and a negative correlation between Rothiaand WBC in the mild group. Acinetobacter, Actinomyces, Corynebacterium, Rothia and Streptococcus were negatively correlated with CRP in the severe group, but there was no correlation between top 10 genera and CRP in the mild group (Fig. 7C, D).