3.1 Study parameters
In this trial, 80 patients were enrolled and randomized into two groups of 40 patients each. Sixteen patients did not complete the study, ten were lost to follow-up, and six did not comply with the required consecutive intervention. The final analysis included 64 individuals, of which 33 were in the probiotic group and 31 were in the placebo group (Figure 1).
3.2 Baseline characteristics of the participants
The baseline characteristics of the participants are presented in Table 1. There were no statistically significant differences in age, sex, body mass index (BMI), or fecal consistency between the groups (p> 0.05). The population with constipation comprised more women (75%) than men (25%). The participants were considered to have functional constipation according to the Rome IV criteria. Differences in functional constipation parameters PAC-SYM, PAC-QOL, BSFS, and N0. BM/week at baseline were insignificant (p>0.05).
Table. 1. Demographic and baseline characteristics of participants in the clinical trial.
Characteristics
|
Placebo (n=31)
|
Probiotic (n=33)
|
P value
|
Sex (male/female)
|
6 (0.19)/25 (0.81)
|
10 (0.30)/23 (0.70)
|
p>0.05
|
Age (year) (mean ± SD)
|
36.5 ± 15.53
|
39.03 ± 15.15
|
BMI (kg/m2) (mean ± SD)
|
22.1 ± 3.2
|
22.5 ± 3.1
|
PAC-QOL (mean ± SD)
|
72.94 ± 17.68
|
70.55 ± 16.73
|
PAC-SYM (mean ± SD)
|
1.40 ± 0.53
|
1.35 ± 0.52
|
No. of BMs/week (mean ± SD)
|
2.58 ± 0.56
|
2.55 ± 0.62
|
BSFS (mean ± SD)
|
2.68 ± 0.91
|
2.52 ± 0.71
|
Data were presented as mean ± SD. BMI, body mass index; bpm, beats per minute; BSFS, Bristol stool form scale; No. of BMs/week, number of bowel movements per week; PAC-QOL, patient assessment of constipation quality of life; PAC-SYM, patient assessment of constipation symptoms; SD, standard deviation. There were no statistically significant differences across the three groups.
3.3 Clinical efficacy analysis
Sixty-four participants were included in the efficacy analysis, with SCBM as the primary efficacy endpoint and the BSFS Stool Scale as the secondary efficacy endpoint. At the end of the 4-week intervention, there was a significant increase in the number of bowel movements (5.12±1.71) in the probiotic group (p<0.01) compared to the placebo group (3.77±1.56). The Bristol stool form scale of constipated patients in the probiotic group also significantly improved at week 4 (4.20±0.82) compared to week 0 (2.48±0.67). The probiotics showed more effectiveness; this effect started to show at week 2 (p<0.05) and was more pronounced at week 4 (p<0.01). This suggests that probiotic treatment is more favorable than placebo to improving symptoms associated with constipation in patients.
After 4 weeks of intervention, patients with constipation in both the probiotic and placebo groups experienced symptomatic relief. PAC-SYM scores were significantly lower (0.80±0.13) in the probiotic group compared to baseline (1.35±0.51). Although there was an interaction between time and the group of PAC-SYM scores (p<0.05), the separate effect of the group was not statistically significant. PAC-QOL scores were substantially lower in both the probiotic and placebo groups compared to the baseline level, but there was no significant difference (p>0.05), which may be attributed to the placebo effect (Table 2 and Figure 2).
Table. 2. Changes from baseline in clinical efficacy parameters of functional constipation in participants receiving placebo or probiotic capsules.
Score per week
|
Probiotic (n=31)
|
Placebo (n=33)
|
P value
|
Mean ± SD
|
Mean ± SD
|
No. of BM/week
|
Week 0
|
2.42 ± 0.71
|
2.58 ± 0.56
|
0.334
|
Week 1
|
4.55 ± 2.02
|
3.84 ± 1.66
|
0.132
|
Week 2
|
4.76 ± 2.05
|
3.84 ± 1.68
|
0.055
|
Week 3
|
5.03 ± 2.02
|
4.39 ± 1.58
|
0.164
|
Week 4
|
5.12 ± 1.71
|
3.77 ± 1.56
|
0.002
|
BSFS average
|
Week 0
|
2.48 ± 0.67
|
2.64 ± 0.88
|
0.412
|
Week 1
|
3.71 ± 1.12
|
3.46 ± 1.16
|
0.390
|
Week 2
|
4.13 ± 1.01
|
3.45 ± 1.03
|
0.010
|
Week 3
|
4.17 ± 0.88
|
3.63 ± 0.68
|
0.008
|
Week 4
|
4.20 ± 0.82
|
3.54 ± 1.01
|
0.005
|
PAC-SYM score
|
Week 0
|
1.35 ± 0.51
|
1.34 ± 0.45
|
0.957
|
Week 2
|
0.86 ± 0.45
|
0.82 ± 0.46
|
0.703
|
Week 4
|
0.55 ± 0.39
|
0.62 ± 0.45
|
0.467
|
PAC-QOL score
|
Week 0
|
70.45 ± 16.87
|
72.13 ± 16.91
|
0.693
|
Week 2
|
52.27 ± 14.66
|
54.58 ± 15.40
|
0.541
|
Week 4
|
49.48 ± 13.34
|
48.10 ± 15.51
|
0.702
|
BSFS, Bristol stool scale; No. of BMs/week, number of bowel movements per week; PAC-QOL, patient assessment of constipation - quality of life; PAC-SYM, patient assessment of constipation - symptoms; S.D., standard deviation. ANCOVA, Bonferroni correction.
3.4 Effects of probiotics on intestinal flora and their products in patients with chronic constipation
3.4.1 Effects on the main intestinal bacteria
We detected Bifidobacterium, Lactobacillus, Enterococcus faecalis, and Faecalibacterium prausnitzii in both groups before and after the intervention by fluorescence quantitative polymerase chain reaction (FQ-PCR) method. The test data showed that the number of Lactobacillus in the probiotic group increased significantly (p<0.05) with no significant changes in the numbers of Bifidobacterium, Enterococcus faecalis, and Faecalibacterium prausnitzii . The number of Lactobacillus in the probiotic group was significantly different from the placebo group after the intervention(p<0.01), which may be related to the fact that the probiotic ingested was Lacticaseibacillus paracasei (Figure 3).
3.4.2 Effects on the structure and composition of intestinal flora
The α-diversity values of pre-intervention (week 0), post-placebo intervention (post-placebo), and post-probiotic intervention (post-probiotic) were analyzed, and the differences in Chao1, Shannon, and Simpson indices among these three groups were not statistically significant (p>0.05). Principal component analysis showed no significant clustering in the flora among the three groups (Figures 4–5).
Figure 6 shows that, at the phylum level, Firmicutes bacterial gates in both groups increased after the intervention compared with the pre-intervention value, with a more pronounced increase in the placebo group and a significant difference between the two groups (post-placebo vs. post-probiotic, p<0.0001). The Actinomycetes phylum was significantly lower in the placebo group after the intervention (week 0 vs. post-placebo, p=0.0053), with a significant difference between the two groups (post-placebo vs. post-probiotic, p=0.0177). At the genus level, more Bifidobacterium spp. were in the post-intervention probiotic group than in the placebo group (post-placebo vs. post-probiotic, p<0.0001). The post-intervention probiotic group showed reduced Bacteroides spp. (week 0 vs. post-probiotic, p=0.0001) and Blautia spp. Post-intervention probiotic group Bacteroides spp. abundance decreased (week0 vs. post-probiotic, p=0.0001), Blautia spp. abundance decreased (week0 vs. post-probiotic, p=0.0213,) Shigella spp. Escherichia-Shigella decreased in abundance (post-placebo vs. post-probiotic, p=0.0257) and Rochesteria spp. increased in abundance (post-placebo vs. post-probiotic, p=0.0202).At the species level, more Clostridium perfringens were in the post-placebo probiotic group than in the intervention group (post-placebo vs. post-probiotic,p=0.037).
3.4.2 Impact of SCFA
Figure 7 shows that probiotic intervention increased total acid production, while the placebo group did not produce the same effect (p<0.01). Acetic acid content (p<0.05) and propionic acid content (p<0.01) increased significantly after intervention with the probiotic, and propionic acid levels were significantly different from the placebo group after the intervention (p<0.05). Butyric acid and valeric acid increased after probiotic intervention, but the difference was insignificant (p>0.05). All data in the placebo group were not statistically different from pre-intervention (p>0.05) (Table 3 and Figure 7).
Table. 3. Changes from baseline in SCFA of functional constipation in participants receiving placebo or probiotic capsules.
Score
|
Probiotic (n=33)
|
Placebo (n=31)
|
P value
|
Mean ± SD
|
P value
|
Mean ± SD
|
P value
|
Total acid
|
Pre
|
7.528 ± 3.083
|
0.008
|
7.739 ± 2.315
|
0.336
|
0.759
|
Post
|
9.564 ± 2.975
|
8.394 ± 2.898
|
0.117
|
AbsΔ
|
2.036 ± 4.140
|
|
0.655 ± 3.730
|
|
0.167
|
Acetic acid
|
Pre
|
4.409 ± 2.322
|
0.017
|
4.612 ± 2.037
|
0.348
|
0.713
|
Post
|
5.754 ± 2.164
|
5.163 ± 2.451
|
0.310
|
AbsΔ
|
1.346 ± 3.061
|
|
0.552 ± 3.220
|
|
0.316
|
Propionic acid
|
Pre
|
1.493 ± 1.139
|
0.029
|
1.444 ± 0.538
|
0.714
|
0.829
|
Post
|
2.117 ± 1.142
|
1.501 ± 0.690
|
0.012
|
AbsΔ
|
0.624 ± 1.571
|
|
0.058 ± 0.869
|
|
0.082
|
Butyric acid
|
Pre
|
1.182 ± 0.939
|
0.764
|
1.232 ± 0.663
|
0.904
|
0.811
|
Post
|
1.246 ± 0.726
|
1.255 ± 0.734
|
0.962
|
AbsΔ
|
0.064 ± 1.217
|
|
0.024 ± 1.083
|
|
0.889
|
Isobutyric acid
|
Pre
|
0.114 ± 0.063
|
0.952
|
1.106 ± 0.066
|
0.504
|
0.633
|
Post
|
0.114 ± 0.062
|
0.118 ± 0.080
|
0.854
|
AbsΔ
|
0.001 ± 0.084
|
|
0.012 ± 0.098
|
|
0.629
|
Valeric acid
|
Pre
|
0.148 ± 0.094
|
0.840
|
0.158 ± 0.116
|
0.542
|
0.688
|
Post
|
0.153 ± 0.995
|
0.175 ± 0.120
|
0.413
|
AbsΔ
|
0.005 ± 0.140
|
|
0.0169 ± 0.153
|
|
0.745
|
Isobutyric acid
|
Pre
|
0.183 ± 0.110
|
0.876
|
0.188 ± 0.140
|
0.842
|
0.861
|
Post
|
0.179 ± 0.094
|
0.181 ± 0.115
|
0.934
|
AbsΔ
|
0.004 ± 0.135
|
|
0.007 ± 0.194
|
|
0.936
|
Student's t test.
3.5 Effect of probiotics on fecal metabolome in patients with chronic constipation
We investigated the alterations in fecal metabolites in patients with chronic constipation using a non-targeted LC-MS-based metabolomics method to determine the metabolic pathways and biomarkers most pertinent to understanding and treating disorders associated with constipation. Partial Least Squares Discriminant Analysis (PLS-DA) was used to predict the sample categories. The R2 and Q2 values of the PLSDA permutation test plots were lower than the initial R2 and Q2 values on the upper right, indicating a robust model (Figure 8).
3.5.1 Effects on fecal metabolites
Using the PLS-DA multivariate statistical method and setting VIP (Projection of Importance Value of the First Principal Component Variable of PLS-DA) as >1 and p<0.05, 81 secondary differential metabolites were obtained, of which 41 were upregulated and 40 were downregulated (see Appendix). Differential metabolites associated with constipation were as follows: fecal metabolism associated with bile acid metabolism was significantly higher for 3-sulfinoalanine, significantly higher for prostaglandin I2, and lower for 8(S)-HPETE after the probiotic intervention compared to the pre-intervention. In addition, 3-methylindolepyruvate associated with caffeine metabolism, sphingosine associated with sphingolipid metabolism, and O-phosphoethanolamine were elevated, and lanosterin, 24,25-dihydrolanosterol, stigmasterol, and 24-methylenecycloartanol were decreased (Figure 9).
3.5.2 Effects on fecal metabolite enrichment
Figure 8A shows the pathway enrichment of the top 20 pathways associated with constipation before and after the probiotic intervention. The pathways closely related to constipation were taurine and hypotaurine metabolism, primary bile acid biosynthesis, caffeine metabolism, and tryptophan metabolism. Other pathways include sphingolipid metabolism, amino acid metabolism, nerve-mediated signaling pathways, protein digestion and absorption, and phenylalanine metabolism. It can be seen that probiotics produced beneficial effects mainly through bile acid metabolism, caffeine metabolism, and tryptophan metabolism pathways.
3.6 Correlation analysis of metabolic differentials with gut differential flora
Using Spearman's correlation analysis, we correlated the above differentially enriched metabolites for significant metabolic pathway correlations with the screened genus-level intestinal differential bacterial flora (Figure 8B). A cluster heat map was created using the obtained correlation coefficients. The results of the correlation analysis showed that Bacteroides abundance positively correlated with stigmasterol (p<0.01), and Blautia abundance positively correlated with 5-aminolevulinic acid (p<0.05) and negatively correlated with stigmasterol (p<0.05). The abundance of Roseburia bacteria was positively correlated with O-phosphoethanolamine and 3-methylxanthine (p<0.05) and negatively correlated with N-acetylputrescine, triethanolamine, and 3-methylindolepyruvate. Escherichia-Shigella abundance was positively correlated with 3-methylindolepyruvate and 2-arachidonoylglycerol (p<0.05) and negatively correlated with 8(S)-HPETE (p<0.05).