Gut microbiome has been identified in the past decade as an important factor involved in obesity, but the magnitude of its contribution to obesity and its related comorbidities is still uncertain. Among the vast quantity of factors attributed to obesity, environmental, dietary, lifestyle, genetic, and others, the microbiome has aroused curiosity, and the scientific community has published many original articles. Most of the studies related to microbiome and obesity have been reported based on the associations between microbiota and obesity, and the in-depth study of the mechanisms related has been studied mainly in rodents and exceptionally in humans. Due to the quantity and diverse information published, the need of reviews is mandatory to recapitulate the relevant achievements. In this systematic review, we provide an overview of the current evidence on the association between intestinal microbiota and obesity. Additionally, we analyze the effects of an extreme weight loss intervention such as bariatric surgery on gut microbiota. The review is divided into 2 sections: first, the association of obesity and related metabolic disorders with different gut microbiome profiles, including metagenomics studies, and second, changes on gut microbiome after an extreme weight loss intervention such as bariatric surgery.
Obesity is known to be a major public health problem that affects more than 1.9 billion adults, which means 39% of adults are considered obesity and overweight [
The latest public statements report the attributable deaths to obesity. The Global BMI Mortality Collaboration reported that mortality increased with body mass index (BMI) approximately in a log-linear manner and that the associations of both overweight and obesity with higher all-cause mortality were broadly consistent in four continents [
Another troubling factor is the increase of childhood obesity, which is known to be a risk factor for obesity in adults [
Gut microbiota has captured our attention in the last decade as an element that directly affects our health or disease status. In particular, it has been implicated in the aetiology of obesity [
Gut microbiota is considered as an assortment of microorganisms that inhabit the gastrointestinal tract. The composition of this microbial community depends on the host, but it can also be modified by exogenous and endogenous events [
With regard to the host, these bacteria are symbiotic, and play an important role in physiological processes, for example, in digestion, or they can intervene in the metabolism, as they can increase energy production from the diet and take part in the regulation of the fatty acid tissue composition [
With the introduction of human whole metagenome studies, the associations of microbiota and disease were plausible and many have been encountered.
It is known that most of the human’s populations microbiota is composed by 5 phyla Bacteroidetes, Firmicutes, Actinobacteria, Proteobacteria, and Verrucomicrobia [
The composition of the bacterial diversity seems to change between lean and obese, increasing the number of Firmicutes to the detriment of Bacteroidetes [
The new era of sequencers has widely unlocked the acquirement of information. Sequencing of specific regions of 16S or 18S ribosomal genes allows the identification of organisms and their relative abundance in purified DNA [
Bariatric interventions have been implemented as a solution to extreme situations of weight gain in the past decades. The techniques have improved with two main variants: the Roux-en-Y gastric bypass (RYGB) and the laparoscopic sleeve gastrectomy (LSG).
RYGB and LSG procedures modify the anatomy of the gastrointestinal system, which modulates nutrient transit and impacts gut physiology. They are known to produce a long-term reduction in body weight and to decrease blood glucose levels, both of which are relevant to obesity-related type 2 diabetes and cardiovascular disease. Nevertheless, the mechanisms implicated in the metabolic improvements associated with bariatric surgery are still challenging. [
Some studies have pointed to the effect of surgery on the microbiota diversity as a partial contribution to the resolution of the metabolic status of these patients [
This review focuses on the current evidence of the associations between the microbiota profile and the individuals’ phenotypes and on the effect of bariatric surgery on gut microbiota.
We assessed observational human studies or clinical trials that evaluated the gut microbiota of individuals who suffered from obesity. Obesity was defined by body mass index (BMI). We also selected observational studies of extreme weight loss interventions, such as bariatric surgery, but did not include dietary interventions, because there is a lack of homogeneity, and many reviews have already focused on this theme.
We selected the MeSH terms “Obesity” AND “Microbiota,” with the following filters: language: English, French, and Spanish; publication date: 5 years from August 20, 2017. The search was performed in MEDLINE accessed by PubMed. All of them were screened based on the title and abstract.
Other possible articles were screened and searched on the reference lists of the selected articles. With the reading of the title or title and the abstract, we selected observational studies and clinical trials, and systematic reviews, in humans.
General characteristics of the studies are as follows: From the 570 articles retrieved from the search, 83 articles were selected based on the title and abstract to be read in depth. Finally, 15 studies were included and are described in Tables
Lean/obese clinical trials.
Study identification | Description | Population description | Outcomes | |
---|---|---|---|---|
Kasai et al. 2015 [ |
Cross-sectional study | 56 |
Japanese population: 23 BMI < 20 kg/m2 and 33 BMI ≥ 25 kg/m2 |
Bacterial diversity was significantly greater in obese subjects compared with nonobese subjects. |
Microbiota fecal samples | ||||
16S DNA sequencing | ||||
Corresponding OTU identified according to T-RFLP | ||||
Million et al. 2012 [ |
Cross-sectional study | 115 | 68 obese and 47 controls | |
Microbiota fecal samples | ||||
qPCR targeting Firmicutes, Bacteroidetes, | ||||
Haro et al. 2016 [ |
Cross-sectional study | 75 | 39 men and 36 women with CVD within CORDIOPREV study |
F/B ratio changed with the BMI and between genders. |
Baseline fecal samples | ||||
16S rRNA sequencing | ||||
QIIME software | ||||
Lin et al. 2015 [ |
Cross-sectional study | 659 | Healthy Chinese adults |
BMI was not associated with the bacterial community diversity as assessed by alpha diversity in the models. |
Upper gastrointestinal microbial diversity | ||||
16S rRNA sequencing | ||||
HOMIM software | ||||
Angelakis et al. 2015 [ |
Cross-sectional study | 10 | 5 lean subjects: BMI 20.7 |
Firmicutes and Actinobacteria were the most predominant phyla of the bacterial composition of the duodenal microbiota in both groups. |
Duodenal microbiota | ||||
16S rDNA sequencing | ||||
Illumina MiSeq | ||||
Finucane et al. 2014 [ |
Review of 4 different studies Human Microbiome Project (HMP) and MetaHIT | 159 | HMP project: 24 obese (BMI > 30) and 123 lean (BMI < 25) individuals |
The interstudy variability in the taxonomic composition of stool microbiomes far exceeds differences between lean and obese individuals within studies. No quantitative association between the continuous BMI variable and the ratio of B/F. Variation in the relative abundance of F and B is much larger among studies than between lean and obese individuals within any study. MetaHIT and HMP go in the opposite direction [ |
Goodrich et al. 2014 [ |
Cross-sectional study | 977 | Twin population: 416 twin pairs, mostly females, mean age 60.6 ± 0.3 years |
The family Christensenellaceae was significantly enriched in subjects with a BMI < 25 compared to those with BMI > 30. Overall, a majority ( |
Fecal samples from the twins UK population | ||||
16S rRNA | ||||
Illumina MiSeq | ||||
QIIME software | ||||
Bondia-Pons et al. [ |
Cross-sectional study | 50 | 16 healthy monozygotic twin pairs discordant for weight (BMI difference > 3 kg/m2) |
No differences in fecal bacterial diversity were detected when comparing cotwins discordant for weight. We found that within-pair similarity is a dominant factor in the metabolic postprandial response, independent of acquired obesity. |
Fecal samples | ||||
Diversity of the major bacterial groups by using 5 different validated bacterial group-specific DGGE methods | ||||
Murugesan et al. [ |
Cross-sectional study | 190 | 190 unrelated Mexican children |
No statistical significant differences in abundance of phylum. |
Ignacio et al. [ |
Cross-sectional study | 84 | 30 obese, 24 overweight, and 30 lean children (3–11 years old) | |
Hu et al. [ |
Cross-sectional study fecal samples from 67 obese (BMI > 30 kg/m2) and 67 normal (BMI < 25 kg/m2) individuals | 134 | Korean adolescents aged 13–16 years | No significant differences in the Bacteroidetes, Firmicutes, and Proteobacteria populations in samples from normal and obese adolescents at the phylum level, although the proportion of |
T-RFLP reference human fecal microbiota profiling; qPCR: quantitative PCR; CVD: cardiovascular disease; DGGE: denaturing gradient gel electrophoresis.
Bariatric surgery clinical trials.
Study identification | Description | Population description | Outcomes | |
---|---|---|---|---|
Palleja et al. 2016 [ |
Longitudinal observational study | 13 | Participants were recruited for bariatric surgery: BMI > 40 kg/m2 or BMI > 35 kg/m2 with T2D/hypertension | Gut microbial diversity increased within the first 3 months after RYGB and remained high 1 year later. RYGB led to altered relative abundances of 31 species: |
Fecal samples | ||||
Quantification of gut microbiomes at baseline ( | ||||
16S rDNA shotgun sequencing | ||||
Tremaroli et al. 2015 [ |
Clinical trial | 21 | Weight-stable women 9 years after randomization to either RYGB or LSG and matched for weight and fat mass loss |
Significant differences in microbiota composition for RYGB versus OBS samples but not for LSG versus OBS or RYGB versus LSG. |
Fecal samples | ||||
16S rDNA | ||||
Illumina HiSeq 2000 | ||||
Shotgun sequencing | ||||
Damms-Machado et al. 2015 [ |
Clinical trial | 10 | 10 unrelated subjects with obesity grade III at 3 time points: |
Both interventions resulted in changes of the B/F ratio but with an inverse relationship between the main phyla. |
Fecal samples | ||||
SOLiD long-mate-paired shotgun sequencing | ||||
Graessler et al. 2013 [ |
Clinical trial | 6 | 3 men and 3 women, recruited for RYGB |
↓ Firmicutes, Bacteroidetes, Actinobacteria, and Cyanobacteria. However, the ratios of B/F shifted from 0.99 to 1.31, showing an apparent increase. |
Fecal samples | ||||
16S rDNA | ||||
Illumina HiSeq 2000 | ||||
Shotgun sequencing |
BMI: body mass index, expressed as kg/m2; RYGB: Roux-en-Y gastric bypass; LSG: sleeve gastrectomy.
All the studies had a baseline assessment of the gut microbiota, and the changes in microbial composition were assessed as outcomes.
The 11 studies compared a baseline assessment of gut microbiota from different individual phenotypes whereas the 4 studies which involved bariatric surgery compared the baseline assessment with the change after surgery at different time points within each subject.
Most of the studies were performed in Europe (75%), America (33%), and Asia (25%).
Several molecular biology techniques were used to assess the characterization of the gut microbiome: denaturing gradient gel electrophoresis (DGGE), fluorescence in situ hybridization probes (FISH), metagenomics shotgun sequencing, and characterization of the 16S rRNA genes in a sample, and groups specific real-time polymerase chain reaction (PCR) are some of the assays. Some studies have made a step forward and published results of functional analysis of the gut microbiota and metabolome. We have focused on the analysis of the diversity of microbiota among BMI.
With regard to the time of publication, more than 50% were published in the last 2 years 2015–2017.
Among the latest studies on microbiota profile between lean and obese patients, several studies searched for differential gut microbiota signatures associated with obesity. We found 11 interesting studies, which compare microbiota in individuals with different BMIs.
The first reported study observed that the bacterial diversity was significantly greater in obese subjects compared with nonobese subjects [
In the case of the individuals who suffered from obesity, there was a strong association with the following bacterial species from the Firmicutes phylum:
Furthermore, a third party was introduced with gender, in a study with the aim at observing differences in microbiota between genders, but reported that the differences in gender could be influenced by BMI [
The methodologies differ between these studies. In our sequence of studies, the three assessments were performed in fecal samples of adult individuals who suffered from obesity comparing with normal weight adult individuals. The two first studies were performed by metabarcoding 16S rRNA [
Two of these studies were performed in Europe and the other one in Asia [
Another two publications analyzed the upper gastrointestinal microbial diversity [
The analysis of the upper gastrointestinal microbial diversity did not find association among the bacterial community with obesity. Alpha diversity was not associated with obesity but beta diversity was. The microbiome was characterized using the 16S rRNA gene DNA microarray (the HOMIM array), which uses 16S rRNA-based oligonucleotide probes printed on glass slides. They also used another approach to search for diversity in the community and found that BMI was not associated with the bacterial community diversity as assessed by alpha diversity in their models after adjusting for multiple potential confounders. However, BMI was significantly associated with the variation in the community composition, as assessed by multiple beta-diversity parameters. As a limitation in this study, the microarray was only semiquantitative and contained a limited number of bacterial species. As a microarray based on the 16S rRNA gene, this assay did not produce data that could be used to determine categories of bacterial functions.
Another study performed in upper gastrointestinal tract, studying the microbiota of duodenum [
A very interesting study [
Other studies have been performed in twin pairs, which provide more information about the heritability of microbiota: one of the studies analyzed fecal samples of healthy monozygotic (MZ) twin pairs which were discordant in weight and compared them with other concordant BMI twin pairs [
The most heritable taxon overall was the family Christensenellaceae (Firmicutes phylum), which associates with a low BMI. The family Christensenellaceae was significantly enriched in subjects with a lean BMI (<25) compared to those with an obese BMI (>30).
Within the three most dominant bacterial families, from the Firmicutes phylum and families Ruminococcaceae and Lachnospiraceae, there was a significantly greater similarity for MZ twins compared to dizygotic (DZ) twins, in contrast with the Bacteroidaceae family, in which MZ and DZ twins had similar pairwise diversity. Therefore, Firmicutes seems to have more heritability.
Three studies have focused their attention on gut microbiota association to obesity in children. Two of them were performed in Central and South America in children up to 11 years old. Another study performed in youngsters aged 13–16 was performed in Asia.
A Mexican study [
The genus
In contrast, another study in Korean adolescents did not find any significant differences in the Bacteroidetes, Firmicutes, and Proteobacteria populations in samples from normal and obese adolescents at the phylum level [
With regard to the metabolically healthy obese subject, defined as those subjects which have normalized levels of the parameters that are used to define metabolic syndrome (blood pressure, HDL cholesterol levels, glycaemia, and visceral fat), there is no literature characterizing the microbiota profile of these subjects. Such findings would be interesting to understand whether the microbial diversity has a metabolic role in individuals who suffered from obesity.
We have found 4 articles in the last 5 years to look for the effect of bariatric surgery on the microbiota profile. All four studies analyze the results comparing with a baseline before the intervention and have a follow-up of 6 months to 1 year. Two of them studied the changes after RYGB surgery, another one LSG, and another one included both types of surgery.
Palleja et al. found that after RYGB surgery, the microbial diversity increased and this diversity was maintained one year after surgery [
Opposite to this assumption, another study in which BS was LSG, compared to a diet, showed that both interventions resulted in changes of the Bacteroidetes/Firmicutes ratio but with an inverse relationship between the main phyla [
Finally, another study that only recruited patients with a RYGB found that four of the top seven high abundance phyla were decreased in postoperative samples, including Firmicutes (from 47.2 to 34.2%), Bacteroidetes (from 46.9 to 44.7%), Actinobacteria (from 1.7 to 1.2%), and Cyanobacteria (from 0.10 to 0.06%). However, the ratios of Bacteroidetes/Firmicutes shifted from 0.99 to 1.31, showing an apparent increase.
This review intends to recapitulate the information obtained in the last 5 years on the association of gut microbiota with obesity and an extreme weight loss intervention. One of the important points of discussion is whether obesity is associated with more or less microbiota diversity and whether the ratio F/B is increased with obesity.
Still some controversial data have been published in the past 5 years. Whereas previous relevant studies [
Among the presented studies, one study observed an increase in alpha diversity which was also related to an increase in the ratio F/B [
Among the limitations of the studies, the new and growing advance in methodologies such as next-generation sequencing has arouse many different possibilities in terms of laboratory work and data management and software, as mentioned above in a comparative study [
This review systematically assessed studies of association between obesity and microbial diversity of the gastrointestinal tract and bariatric surgery interventions in obese and overweight patients. Obesity is associated with different profiles of gut microbiota, but studies seem not to find enough consistency on the results, most probably because it can be influenced by several factors, among them the different methodologies and growing data management knowledge. Also, we review that bariatric surgery intervention for weight loss impacts the gut microbiota composition.
Further trials and the evolution of this shotgun sequencing data management are needed to draw conclusions about the role of microbial diversity in obesity.
There is no competing interest involving any of the authors of this manuscript.
Helmut Schröder and Olga Castaner conceived the study, participated in its design, literature search, and collation of all drafts, and drafted the manuscript; Albert Goday, Yong-Moon Park, Seung-Hwan Lee, Faidon Magkos, and Sue-Anne Toh Ee Shiow contributed to the manuscript draft. All authors read and approved the final version of the manuscript.
This article was supported by OCN Grants JR14/0008 and JR17/00022 from ISCIII. CIBEROBN is an ISCIII initiative. CIBERESP is an ISCIII initiative.
Figure 1: PRISMA-based flowchart of all the records searched.