Using a newly developed metagenome-wide association study approach, an international team led by investigators at BGI-Shenzhen and the University of Copenhagen has come up with a set of type 2 diabetes-associated microbial gene markers in the human gut that may eventually lead to gut microbe-based methods for diagnosing the disease.
"This is a promising way to diagnose T2D," BGI-Shenzhen researcher Junjie Qin told Clinical Sequencing News in an email message.
"At least, we [know] what gut bacteria is good and what is harmful for type 2 diabetes, so we can control diet or other life habits by monitoring our gut bacteria," explained Qin, who was co-first author on a study published in the Oct. 4 issue of Nature.
For that paper, Qin and his colleagues sequenced gut microbial DNA from stool samples obtained from hundreds of Chinese individuals with or without T2D. In addition to plumping up the set of microbial genes that have been detected in the human gut, they used the metagenomic sequence data as part of a two-stage MGWAS. The latter analysis looked for T2D-associated microbial genes, pathways, and sets of microbial sequences dubbed "metagenomic linkage groups" that represent both known and unknown bacterial species.
The group's findings suggest that individuals with T2D tend to have fewer bugs that produce the potentially beneficial fatty acid metabolite butyrate, for instance. On the other hand, T2D-associated gut microbiomes showed a rise in sequences corresponding to known opportunistic pathogens such as Escherichia coli or several Clostridium species.
Although the team identified tens of thousands of apparent microbial markers for T2D in its MGWAS, follow-up experiments on another 11 T2D cases and a dozen controls demonstrated that a gene index based on 50 gene markers could accurately distinguish between individuals with and without T2D.
"Our data provide insight into the characteristics of the gut metagenome related to T2D risk, a paradigm for future studies of the pathophysiological role of the gut metagenome in other relevant disorders, and the potential usefulness for a gut-microbiota-based approach for assessment of individuals at risk of such disorders," the study's authors noted.
To further explore the diagnostic potential of gut microbial markers, the team plans to do functional experiments, combined with studies that track gut microbial communities over time in individuals who appear to be at risk of T2D but who have not yet developed the disease.
"We will test the predictive power of these markers in longitudinal studies, for example, at the stage of pre-diabetes," Qin said. "We also plan to use animal experiments to test the causal relationship between these metagenomic markers and type 2 diabetes."
On that front, researchers plan to transplant gut microbes from individuals with T2D into mice to determine whether the presence of these bugs can bring on T2D in previously healthy animals, co-author Oluf Pedersen, a biology researcher with the University of Copenhagen, the University of Aarhus, and Denmark's Hagedorn Research Institute, explained in a statement.
"It is important to point out that our discovery demonstrates a correlation," co-author Karsten Kristiansen, a biology researcher affiliated with the University of Copenhagen and BGI-Shenzhen, added in a statement. "The big question now is whether the changes in gut bacteria can affect the development of type 2 diabetes or whether the changes simply reflect that the person is suffering from type 2 diabetes."
While most genetic studies of T2D risk have focused on variants present in the host genome, Qin and his co-authors explained, some recent research hints that the nature and diversity found in gut microbial communities differs with obesity, Crohn's disease, T2D, and other conditions.
Such findings have sparked interest in uncovering gut microbiome-based markers for diagnosing various diseases.
Last year, for instance, investigators involved in a large European study of gut microbial metagenomics known as MetaHIT (IS 6/24/2008) launched a translational research company called Enterome.
The Paris-based startup, which is collaborating with the French National Institute for Agricultural Research (INRA) and other academic centers, aims to develop and commercialize gut microbial biomarkers for diabetes, non-alcoholic fatty liver disease, inflammatory bowel disease, and other metabolic and bowel-related conditions (CSN 4/11/2012).
INRA researcher and MetaHIT coordinator Dusko Ehrlich, who was named chief scientific officer and scientific founder of Enterome, was among the co-authors on the current study.
CSN reached Ehrlich by email. He did not comment directly on whether Enterome has its sights set on commercializing microbial markers described in the paper, but said that discussions between BGI and Enterome regarding biomarker development, particularly related to metabolic diseases, have been motivated by "clear complementarities" between the groups, both "in activities and geographic spheres."
At the moment, Ehrlich said, such projects are being examined on a case-by-case basis.
Before looking for gut microbe patterns that coincided with T2D status for the current study, the researchers started by adding to MetaHIT's existing gut microbial gene reference set, using metagenomic sequence data from DNA in fecal samples from 71 Chinese individuals with T2D and 74 unaffected controls from the same population.
For each of the samples, the team generated between around 15 million and 30 million paired-end reads on the Illumina GAIIx or HiSeq 2000 platforms.
In situations where a disease state is linked to the presence or absence of microbes found at very low abundance it will likely be necessary to generate more reads per sample, Qin noted.
For the current analysis, though, the available reads appeared to be sufficient to account for all but the rarest microbial community members, he explained, and to pick up differences between healthy gut microbiomes and those associated with T2D.
"In our experience, the read number and the sample number are both determined by the type of disease to be studied," Qin said via email.
The researchers identified more than 1 million new gut microbial genes in the 145 discovery set samples, which were covered by 15.8 paired-end reads apiece, on average. Adding this data to the MetaHIT gene catalog brought the tally of predicted microbial genes that have been detected in the human gut up to nearly 4.3 million.
In addition to defining genes and pathways present in the microbial communities using information on bacterial reference genomes and gene ortholog data from available databases, the team went on to use the metagenomic sequence data in analyses of gut microbe-related associations with T2D.
In general, Qin said, the MGWAS approach is comparable to that used for conventional GWAS, though the computational strategy is modified somewhat to deal with metagenomic sequence information rather than SNP data.
First, the team determined the relative abundance of the various microbial sequences found in individuals' stool samples, using data for sequences that mapped with at least 90 percent identity to the updated gut microbe gene sequence set.
Similar to findings in European populations (GWDN 4/20/2011), the researchers uncovered three gut microbial community enterotypes in the Chinese individuals tested. But, they noted, none of the enterotypes showed significant ties to T2D status.
On the other hand, the investigators' MGWAS analyses indicated that there were significant links between T2D and levels of certain microbial genes in the gut — findings that they verified through metagenomic sequencing experiments on samples from 200 more Chinese individuals with or without diabetes.
Because just over one-fifth of the gut microbial genes included in the expanded reference set could be traced back to a known bacterial genus, the researchers considered sets of T2D-associated genes in packages known as metagenomic linkage groups, which are expected to account for both known and unknown species.
"Here a [metagenomic linkage group] is defined as a group of genetic material in a metagenome that is probably physically linked as a unit rather than being independently distributed," the study's authors explained.
"[T]his allowed us to avoid the need to completely determine the specific microbial species present in the metagenome," they added, "which is important given there are a large number of unknown organisms and that there is frequent lateral gene transfer between bacteria."
As such, Qin said, the sequences comprising a given metagenomic linkage group are expected to remain more or less consistent from one study to the next.
In the T2D MGWAS, for instance, the team detected genes from 47 metagenomic linkage groups that were found at different levels in individuals with T2D than in healthy controls.
The metagenomic linkage groups that were more common in those with diabetes included groups representing 17 known bacterial species, researchers reported. Among them: several opportunistic pathogens such as E. coli, Bacteroides caccae, and Clostridium species, along with species known for their sulfate-reducing or mucin-degrading skills.
In contrast, gut microbial communities in the healthy control group were more apt to contain butyrate-producing bugs such as Clostridiales sp. SS3/4 or Eubacterium rectale.
Still other, yet uncharacterized, organisms turned up in both the T2D and control groups.
The researchers have already started to unravel the metabolic capabilities of the T2D-associated gut microbial communities relative to those found in healthy controls. For instance, at the functional level, they found a preponderance of T2D-associated sequences believed to code for components of transport pathways that move sugars and some amino acids.
The disease-associated communities were also more likely to harbor genes or gene orthologs from pathways related to methane metabolism, sulfate reduction, oxidative stress resistance, drug resistance and so on.
Pathways favored by microbes in the healthy control individuals' guts, on the other hand, included those contributing to butyrate, vitamin, and co-factor production processes, bacterial chemotaxis, motility, and flagella assembly.
In a follow-up experiment involving 11 individuals with T2D and a dozen unaffected controls, the team reported it was possible to distinguish between those with or without disease based on a T2D index comprised of 50 gut microbial gene markers. But more research is needed to determine whether these or similar markers can pick up individuals at risk of the disease prior to its onset.
"Overall, our cross-sectional study in overt T2D indicated that it would be worthwhile to test more extensively gut-microbiota-based classifiers in future longitudinal studies for their ability to identify subsets of the population that are at high risk for progressing to clinically defined T2D," the authors argued.
Additional longitudinal studies should also help in teasing apart the biological basis for the relationship between T2D disease state and the microbiome, Qin explained — particularly in terms of understanding which microbiome features contribute to disease symptoms and development, if any, and which are a consequence of T2D itself.
In addition, Qin said the team has already kicked off a project looking at the interplay between the gut microbiome, T2D, and obesity.
Researchers at BGI are also collaborating with several other research groups to do MGWAS for additional diseases that may be influenced by microbial communities associated with the body, according to Qin.
"[W]e have many collaborators with different backgrounds," he explained, "and they are very interested in many kinds of disease."