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Herbal medicine is a low-cost treatment and has been increasingly applied in obesity treatment. Gut microbiota (GM) is strongly associated with obesity pathogenesis. Schisandra chinensis and Scutellaria baicalensis had significant effects on weight loss herbal intervention therapy composed by five Chinese herbal medicines Ganoderma lucidum, Coptis chinensis, Astragalus membranaceus, Nelumbo nucifera gaertn, and Fructus aurantii (W-LHIT) and white common bean extract (WCBE) on GM, but no significant changes in anthropometry and laboratory biomarkers.
- gut microbiota
- herbal medicine
- obesity
- overweight
1. Introduction
Obesity is currently a metabolic disease associated with an increased risk for the emergence of other diseases, such as type 2 diabetes mellitus and cardiovascular disease, leading causes of death worldwide [1]. In 2016, the World Health Organization [2] estimated that more than 1.9 billion adults were overweight.
The primary strategies for obesity treatment encourage changes in lifestyle, such as shifting to a healthy eating pattern, rich in natura or minimally processed foods, and regular physical exercise, among others. There is a thriving interest in medicinal plants for the prevention and treatment of different diseases, including endocrine ones, even though the Eastern world has been using them for centuries [3]. In this context, herbal medicine can play an important role in obesity treatment through mechanisms, such as stimulating thermogenesis, inhibiting pancreatic lipase activity, reducing food intake, reducing fat absorption, increasing lipolysis and decreasing lipogenesis [4]. These actions are associated with the presence of secondary metabolites featured in plants, such as flavonoids, saponins, and essential oils, among others, which trigger important physiological changes [5]. In this way. Thus, herbal medicine shows conceivable therapeutic benefits toward metabolic disorders [6], opening other paths through the treatment of obesity.
Human GM has been included in the list of factors studied in relation to obesity, as well as other comorbidities [7]. Gut microorganisms, including bacteria, archaea, fungi, and viruses, may impact the development of metabolic disorders in different ways, such as by altering dietary energy production, causing imbalance in the composition of adipose tissue, affecting inflammatory processes, causing intestinal barrier disruption, as well as affecting the regulation of appetite through the gut–brain axis [8].
The interaction between herbal medicine and GM can occur in multiple ways. One mechanism is by altering the composition and function of microorganisms, specifically bacteria [9]. Another mechanism involves the action of metabolites derived from medicinal plants during the metabolic process in the body [10]. Hence, the modulation of the GM through herbal medicines [11] represents a novel frontier for developing medicines or drugs to treat obesity.
2. Results of Search
In the preliminary stage of searching for articles, researchers retrieved 1094 records from the databases. After removing the duplicates, 790 titles and abstracts were screened in accordance with the inclusion criteria. Therefore, 14 publications were fully evaluated, 7 of which were excluded.
There was an attempt to contact the authors of one study with insufficient data on the GM results. Finally, seven publications from six studies were included in the review. Figure 1 shows an overview of the screening procedure.
Figure 1. PRISMA study flow diagram for search up to April 2023.
3. Study Characteristics
Five studies were double-blind, parallel randomized clinical trials, and the other two had a crossover design [12][13][14][15]. They were published between 2015/2023 and carried out in three countries: China, South Korea, and Spain. The individuals’ ages ranged from 20 to 75 years old. One study [15] included only females, while the others encompassed both sexes. Two studies were limited to the overweight population. It is noteworthy that two complementary publications of the same study were found and were considered as one [16][17].
The herbal medicines studied were Moringa oleifera [14], Punica granatum [16][17], Scutellaria baicalensis [18], Schisandra chinensis [15], and weight loss herbal intervention therapy consisting of five Chinese herbal medicines: Ganoderma lucidum, Coptis chinensis, Astragalus membranaceus, Nelumbo nucifera gaertn, and Fructus aurantii (W-LHIT) [12], and white common bean extract (WCBE) [13].
In the study by Goméz-Martinéz et al. [14], Moringa oleifera was offered in 400 mg/capsules. The participants were instructed to take two capsules before the three main meals (breakfast, lunch, and dinner) for 12 weeks. Morbid obesity (body mass index, BMI > 35 kg/m2) was used as an exclusion criterion.
The study by González-Sarrías et al. [16][17] has a crossover design. Participants received a daily dose of 450 mg of Punica granatum for three weeks, followed by a three-week washout period, and then another daily dose of 1800 mg for three weeks. Although the clinical trials treated the same population, they differ in their approaches and research methods regarding GM, being complementary in their results.
In the Shin et al. study [18], Scutellaria baicalensis was tested in association with the use of metformin in a crossover trial. The dosage given was 3.520 mg/day for eight weeks, followed by a wash-out period of four weeks, and a further eight weeks with a placebo. In both periods, the dosage of metformin was maintained according to the previous medical prescription of each participant. In the study conducted by Song et al. [15], participants consumed Schisandra chinensis in liquid form, provided in bags of 100 mL (two units) containing approximately 6700 mg of dry extract per day for a duration of eight weeks.
Extraction from white common beans (Phaseolus vulgaris) was applied in the study of Feng [13], being offered in doses of 1.5 g for each meal daily over the course of 4 months.
The other Chinese clinical trial by Cao [12] prescribed capsules composed of five herbs (Ganoderma lucidum, Coptis chinensis, Astragalus membranaceus, Nelumbo nucifera gaertn, and Fructus aurantii). The intervention group dosage was based on individual body weight, varying from 9 to 15 capsules a day for two months. Table 1 describes the details of each study.
Table 1. Characteristics of the studies included in the systematic review.
| Author, Country |
Age (Years) | BMI (kg/m2) |
Gender | Comorbities | nB/N Endpoint (% Dropout) |
Intervention/Control | Dosage | Duration |
|---|---|---|---|---|---|---|---|---|
| Cao [12] China |
18 to 60 | 32.25 ± 1.4 (intervention) 34.04 ± 2.5 (control) |
M: 24; F: 13 |
- | 37/40 (7.5%) |
W-LHIT | 9 to 15 capsules/day | 2 months |
| Feng [13] China |
35 to 75 | 27.9 ± 0.4 (intervention) 25.1 ± 0.5 (control) |
M: 33; F: 50 |
Diabetes T2D | 83/96 (13.5%) |
WCBE | 1.5 g before each meal/day |
2 months |
| Gómez-Martínez [14] Spain |
45 to 70 | 28.6 ± 3.8 (intervention) 29.4 ± 4.0 (control) |
M: 29; F: 36 |
Prediabetes | 73/65 (11.0%) |
Moringa oleifera |
2.4 g/day | 12 weeks |
| González-Sarrías, [16][17] Spain |
>40 | 28.5 ± 1.1 overweight 33.2 ± 3.3 obese |
M: 32; F: 17 |
- | 50/49 (2.0%) |
Punica granatum |
0.45 g/day (3 weeks) 1.8 g/day (3 weeks) |
24 weeks (3 weeks of wash out between dosage) |
| Shin [18] South Korea |
20 to 75 | 25.62 ± 0.64 (intervention) 25.69 ± 0.62 (control) |
F and M |
Diabetes T2D | 17/12 (29.4%) |
Scutellaria baicalensis |
3.52 g/day | 8 weeks (4 weeks of wash out) |
| Song [15] South Korea |
25 to 45 | 29.99 ± 4.27 (intervention) 28.78 ± 3.47 (control) | F | - | 40/28 (30.0%) |
Schisandra chinensis | 6.7 g/day | 12 weeks |
4. Gut microbiota
GM research was highlighted as the main outcome in five articles [12][13][16][17][18], while two others placed it as a secondary outcome [14][15]. Table 2 describes the main finding of microbiota analysis.
Table 2. Changes of the GM following the administration of herbal medicines in overweight and obese individuals.
| Article | Intervention | Microbiota Analysis Method | GM Changes |
|---|---|---|---|
| Cao [12] China |
9 to 15 capsules W-LHIT/day | 16S rRNA | Increase in phylum Verrucomicrobia, and decrease in phylum Proteobacteria. Increase in genera Akkermansia and Enterococcus. Decrease in species Eubacterium rectale, Haemophilus parainfluenzae, and Faecalibacterium prausnitzii. |
| Feng [13] China |
1.5 g WBCE before each meal/day | 16S rRNA | Increase in genera Anaerostipes, Bifidobacterium, Faecalibacterium, Faecalitalea Lactobacillus, and Romboutsia, and decrease in genera Adlercreutzia, Citrobacter, Cronobacter Enterobacteriaceae, Fusobacterium, Klebsiella, and Weissella. |
| Gómez-Martínez [14] | 2.4 g dry extract MO/day 12 weeks |
16S rRNA | No significant change in Clostridium cluster IV and in genera Bifidobacterium and Lactobacillus. No significant change in species Blautia coccoides, Eubacterium rectale, Faecalibacterium prausnitzii, and Akkermansia muciniphila. |
| González-Sarrías [16] | 0.45 g dry extract PG/day 3 weeks 1.8 g dry extract PG/day 3 weeks |
real-time qPCR | Increase in genera Gordonibacter and Bacteroides. Increase in species Escherichia coli. |
| González-Sarrías [17] | 0.45 g dry extract PG/day 3 weeks 1.8 g dry extract PG/day 3 weeks |
16S rRNA | Increase in phylum Bacteroidetes, and decrease in phylum Firmicutes. Increase in families Bacteroidaceae and Porphyromonadaceae, and decrease in families Peptostreptococcaceae, Clostridiaceae, and Coriobacteriaceae. Increase in genera Bacteroides and Faecalibacterium, and decrease in genera Romboutsia, Anaerostipes, Dorea, and Clostridium sensu stricto. No significant changes in bacterial diversity. |
| Shin [18] | 3.52 g dry extract SB/day 8 weeks |
16SrRNA | Increase in genera Lactobacillus, Weissella, and Akkermansia. No significant changes in bacterial diversity. |
| Song [15] | 6.7 g dry extract SC/day 12 weeks |
qPCR | Increase in phylum Bacteroidetes, and decrease in phylum Firmicutes. Increase in genera Akkermansia, Roseburia, Bacteroides, Prevotella, and Bifidobacterium; decrease in genus Ruminococcus. |
Clinical trials with W-LHIT [12], WCBE [13], Punica granatum [17], Scutellaria baicalensis [18], and Moringa oleifera [14] used 16srRNA metagenomic technology for the analysis of GM. The other clinical trials [15][16] collected data using the qPCR technique.
The study by González-Sarrías consisted of two separate publications, each utilizing different approaches for the analysis of the GM. In the first publication, which employed the qPCR technique [16], there was a significant increase in the genera Gordonibacter, Bacteroides, and Escherichia coli, alongside a reduction in lactic acid bacteria. The research on the GM has focused on bacteria involved in the conversion of secondary metabolites to urolithin, narrowing its spectrum of bacterial analysis.
The other publication [17] sought to observe broader alterations in the GM with the use of Punica granatum, in addition to verifying changes in the endotoxemia. For the interventional group, at the phylum level, there was an increase in Bacteroidetes and a decrease in Firmicutes. There was also an increase in Bacteroides and Faecalibacterium genera, with a reduction in Romboutsia, Anaerostipes, Dorea, and Clostridium sensu stricto. At the family level, there was an increase in Bacteroidaceae and Porphyromonadaceae, and a reduction in Peptostreptococcaceae, Clostridiaceae, and Coriobacteriaceae.
The same phylum change was also observed in the clinical trial conducted by Song using Schisandra Chinensis as an intervention [15], which led to a subsequent reduction in the Firmicutes/Bacteroidetes ratio. At the genus level, the intervention group showed an increase in Akkermansia, Roseburia, Bacteroides, Prevotella, and Bifidobacterium, while only Ruminococcus exhibited a decrease compared to the placebo group.
In the trial that combined Scutellaria baicalensis with metformin [18], there was an increase in the abundance of Megamonas, Mobilitalea, Acetivibrio_g1, Lactobacillus, and Akkermansia. Conversely, a decrease in Clostridium_g23, Oscillibacter, Alloprevotella, and Bifidobacterium was observed. The Weissella genus did not show any significant change in either the treatment or control groups.
The use of Moringa oleifera [14] as a strategy for glycemic control did not find changes in the GM composition for Bacteroides, Blautia coccoides, Eubacterium rectale, Clostridium cluster IV, Bifidobacterium spp., Lactobacillus spp., and Enterobacteriaceae. After the consumption of Moringa oleifera, the only bacterial group to show an increase was Enterococcus spp. However, there were no significant changes observed in the levels of Faecalibacterium prausnitzii and Akkermansia muciniphila, which are considered bacterial species markers of gut health.
5. Anthropometric and Biomarkers Data
Researchers sought to identify outcomes related to the anthropometry and laboratory biomarkers of the selected clinical trials. As well as the GM data, the articles presented varied data. These divergences result in comparative limitations. Table 3 presents the results for the parameters evaluated. When comparing the effects of the evaluated herbal medicines, no significant changes were observed in any variable.
Table 3. Anthropometric data and laboratory biomarkers of the studies included in the systematic review.
| Study (N Intervention/N Control) | Intervention | Control | |||
|---|---|---|---|---|---|
| Cao 2023 (18/19) | Change | SD | Change | SD | Mean difference [CI 95%] |
| Glucose | −0.17 | 0.74 | 0.05 | 0.78 | −0.12 [−0.61, 0.37] |
| C-peptide | −0.5 | 1.23 | 0.1 | 1.33 | −0.40 [−1.22, 0.42] |
| Insulin | −3.87 | 9.78 | −2.1 | 13.33 | −1.77 [−9.28, 5.74] |
| BMI | −1.31 | 1.1 | −0.88 | 0.88 | −0.43 [−1.05, 0.19] |
| Gomez-Martinez 2021 (31/34) | Change | SD | Change | SD | Mean difference [CI 95%] |
| Glucose | −2.80 | 7.8 | 2.0 | 13.2 | −4.80 [−10.02, 0.42] |
| Insulin | 1.26 | 4.02 | 1.82 | 4.24 | −0.56 [−2.57, 1.45] |
| HbA1c | −0.09 | 0.30 | 0.04 | 0.34 | −0.13 [−0.29, 0.03] |
| HOMA | 0.24 | 1.06 | 0.57 | 1.4 | −0.33 [−0.93, 0.27] |
| GLP | −0.80 | 4.93 | −1.4 | 4.75 | 0.60 [−1.76, 2.96] |
| Ghrelin | −47.0 | 66.58 | −42.6 | 65.48 | −4.40 [−36.55, 27.75] |
| PYY | −6.0 | 17.08 | −7.33 | 19.61 | 1.33 [−7.59, 10.25] |
| Shin 2019 (6/6) | Change | SD | Change | SD | Mean difference (CI 95%) |
| Glucose | 3.2 | 4.66 | 5.3 | 4.51 | −2.10 [−7.29, 3.09] |
| Insulin | 0.58 | 0.52 | 0.72 | 0.87 | −0.14 [−0.95, 0.67] |
| HbA1c | 0.05 | 0.13 | 0.03 | 0.14 | 0.02 [−0.13, 0.17] |
| HOMA | 0.21 | 0.13 | 0.29 | 0.26 | −0.08 [−0.31, 0.15] |
| Weight | −0.05 | 1.72 | 0.46 | 1.65 | −0.51 [−2.42, 1.40] |
| BMI | 0.01 | 0.49 | 0.19 | 0.48 | −0.18 [−0.73, 0.37] |
| Waist | −0.22 | 1.28 | 0.54 | 1.28 | −0.76 [−2.21, 0.69] |
| Song 2015 (13/15) | Change | SD | Change | SD | Mean difference (CI 95%) |
| Glucose | −1.31 | 5.86 | 1.0 | 6.1 | −2.31 [−6.75, 2.13] |
| Insulin | −0.41 | 4.26 | −0.64 | 5.98 | 0.23 [−3.58, 4.04] |
| Cholesterol | −1.69 | 24.30 | −5.6 | 20.74 | 3.91 [−12.96, 20.78] |
| HDL | −1.15 | 8.97 | −8.4 | 20.42 | 7.25 [−4.18, 18.68] |
| TG | −27.46 | 109.8 | 11.6 | 45.84 | −39.06 [−103.10, 24.98] |
| Weight | −0.54 | 12.25 | −0.8 | 8.72 | 0.26 [−7.73, 8.25] |
| BMI | −0.2 | 3.42 | −0.33 | 2.82 | 0.13 [−2.21, 2.47] |
| Waist | −1.88 | 6.81 | −1.36 | 7.6 | −0.52 [−5.86, 4.82] |
| %fat | −2.39 | 4.19 | −1.35 | 3.11 | −1.04 [−3.81, 1.73] |
The study by González-Sarrías [16] grouped the results of the surveyed population by type of urolithin (UM-A, UM-B, UM-0) presented in the urine after the clinical trial.
Only two studies reported adverse effects resulting from the consumption of herbal medicines. In the clinical trial conducted by Shin et al. [18] using Scutellaria baicalensis, one of the participants in the intervention group reported epigastric pain. The study by Cao et al. [12] described two subjects with slight gastrointestinal reactions in the treatment group.
This entry is adapted from the peer-reviewed paper 10.3390/nu15092203
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