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New Study Explores Potential Links Between Diet, Microbiome and Immune Response in Multiple Sclerosis

New Study Explores Potential Links Between Diet, Microbiome and Immune Response in Multiple Sclerosis  content piece image
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A new study has adopted a multi-omics methodology to explore potential links between diet, the microbiome and the immune response in multiple sclerosis (MS). The results are published in EBioMedicine.

What is multiple sclerosis? 

Approximately 2.8 million people are estimated to be living with multiple sclerosis (MS) worldwide. It is a potentially debilitating autoimmune disease in which the body’s immune cells attack the myelin sheath that insulates nerves. This sheath is an essential component of the fast electrical signals that let neurons communicate with one another, and its damage subsequently leads to misfiring of nervous signals, or miscommunication.

What are the symptoms of MS?

The clinical symptoms of MS vary between patients and depend largely on the extent of the nerve damage that has occurred. Some individuals may experience tremors, loss of sensation or issues with vision, while others might lose the ability to walk.

The exact reason as to why the immune system aims its defensive mechanisms at the myelin sheath is yet to be confirmed. Current research suggests a host of different factors might be at play, including underlying genetic predispositions and environmental factors. A study of US military personnel published in early January suggested that MS is the result of a complication from Epstein-Barr virus (EBV) infection.

MS and the microbiome – why dietary information is important

Over the last five years, a growing number of clinical research studies have found evidence that the gut microbiome is altered in MS patients when compared to healthy patients. The gut microbiome refers to the collective genomes of the micro-organisms that inhabit our gastrointestinal system. The gut microbiota – the organisms themselves – interact with various systems of the human body to promote health, and in some cases, disease. This includes the immune system.

An issue with previous studies that have gathered data on gut microbiome alterations in MS patients is that they lack information regarding food consumption. “Previous studies barely record diet information, but this is important as diet can affect many things, including the gut microbiome,” says Dr. Yanjiao Zhou, assistant professor of medicine at UCONN Health.

The food that we eat in our diets contributes to the truly unique community of microbes that can be found in each of our guts. In turn, these microbes can have an array of different effects on our immune system – positive and negative. When analyzing the gut microbiome of patients with an autoimmune disorder, it’s therefore necessary to gather data on potentially confounding factors, such as what foods these individuals have been eating to impact that microbiome. This is the focus of Dr. Zhou’s latest research published in EBioMedicine.

Dr. Zhou was one of the lead analysts in the Human Microbiome Project. At UCONN, her laboratory’s focus is developing microbiome-based diagnostic tools and therapeutics for MS and other diseases. In this effort her research group uses a multitude of interdisciplinary multi-omics methods, which they have applied in a new holistic study of the immune status, metabolome, gut microbiome and dietary habits in MS patients and healthy individuals. “It is a biological analysis approach that combines genomics (to study the microbiome), immune profiling (to study immune function) and metabolomics (for studying small molecules),” says Zhou.

What is multi-omics research?

Omics research examines the totality of a molecular component of an organism. It is an integrative method of studying several different research areas, including genomics, proteomics, transcriptomics and metabolomics.

An integrative methodology

Zhou and collaborators, including Dr. Laura Piccio from Washington University, recruited a cohort of 49 volunteers for the study, including 25 MS patients and 24 healthy controls. The majority of the sample were female, and at baseline, none of the MS patients were in active relapse and had not received any disease modifying therapies in the last three months. When assessing lifestyle factors that may differ across the MS group and the control group, the researchers found that the MS group used more tobacco, but there were no other characteristics that different significantly.

The researchers gathered stool and blood samples at baseline and then six months later to conduct analyses on the gut microbiome (using 16s RNA sequencing and metagenomic whole genome sequencing (mWGS), blood metabolome (using ultraperformance liquid chromatography-mass spectrometry, or UPLC-MS) and blood immune cell profiling (using flow cytometry and immunostaining).

Participants were also required to keep a food diary for four consecutive days, providing qualitative self-report data on their diet. This diary was submitted before the stool and blood sample collection at baseline and at the six-month study visit.

Multi-omics analysis of the microbiome, immune cell profile, metabolome and diet

Using the multi-omics approach, the researchers were able to identify several gut bacteria associated with MS and severity of the disease.

When comparing gut microbiome profiles at baseline in MS and control groups – using 16s rRNA gene sequencing followed by mWGS – no significant differences were observed, which “suggests similar overall gut bacterial community structures in the two groups,” the authors write in the paper. However, when focusing their analysis on specific microbes, the researchers found that six species were statistically lower in abundance in MS patients when compared to controls, three of which are recognized as being involved in immunomodulation: Bifidobacterium longum, Clostridium leptum and Faecalibacterium prausnitzii).

Within the MS patient group, the gut microbiome differed significantly by the degree of disability at baseline. This difference remained statistically significant when controlling for bod mass index (BMI).

Zhou and colleagues then sought to identify any differences in the peripheral blood immune cell profiles between groups. Particularly, peripheral blood IL-10+ memory B cells, T-bet+ memory and effector T cells, memory and effector T-helper 17 cells were significantly greater in abundance in MS versus control groups.

Assessment of the food diaries obtained from both the control and MS group did not identify significant differences in diet, although the MS group had a slightly higher meat intake.

“We next sought overall correlations between the gut microbiome, peripheral blood immune and metabolome profiles, and diet, in MS and controls at baseline,” the researchers write in the paper. “The gut microbiome and host blood immune profiles were positively correlated in controls, suggesting a close interaction between the gut microbiome and peripheral immune profiles in healthy controls.” This apparent association was not identified in the MS group, which the authors say could suggest that MS may dissociate immune and microbiome interactions. A positive correlation was, however, found between peripheral immune and metabolome profiles in MS patients, but not in the control group. “The association between immune and metabolome profiles signifies potentially concomitant changes of blood immune cell populations and metabolism in MS patients,” the authors say.

The researchers wanted to explore a hypothesis that an interactive pathway could link diet, gut microbiome, the immune response and the metabolome. MS patients, who reported eating more meat than the control group, had a higher abundance of circulating T-helper 17 cells, identified via immune cell profiling. Zhou and colleagues therefore decided to explore whether a correlation network existed between meat consumption, T-helper 17 cells, the gut microbiome and the blood metabolome.

Higher meat consumption was associated with a decrease in the population of Bacteroides thetaiotaomicron, a species of bacterium that is implicated in the transport and degradation of complex glycans (sugar-based polymers), in the gut. A decrease in B. thetaiotaomicron negatively correlated with abundance of T-helper 17 cells, and the latter positively correlated with concentrations of a metabolite known as methyl donor S-adenosyl-L-methionine,or SAM.

“Our multi-omics analysis suggests a correlation network involving dietary meat serving, gut microbiome, T-helper 17 cells and blood metabolites,” the authors write. “However, our analyses do not indicate the directionality of regulation between each of the aforementioned correlative pair. These results highlight a discovery process driven by omics analysis and provide an interesting hypothesis that now warrants further validation.”

Limitations of the research and future directions

Association studies are useful in this context, Zhou says, because the results can be used to generate hypotheses and encourage future mechanistic studies to test the links that have been identified. However, there are limitations to the study, including the small sample size and self-report nature of collecting data on the participants’ diet. It’s difficult to apply findings from small studies to larger patient populations, and self-report methodologies are recognized as having issues with validity. Furthermore, the study identifies associations – not causations.

The researchers’ next steps involve expanding the study to include a larger sample size. “We are [also] interested in analyzing the microbiome and depression, which we will study next,” Zhou concludes.

Dr. Yanjiao Zhou was speaking to Molly Campbell, Senior Science Writer for Technology Networks.

Reference: Cantoni C, Ghezzi L, Liu Z et al. Alterations of host-gut microbiome interactions in multiple sclerosis. EBioMedicine. 2022. doi: 10.1016/j.ebiom.2021.103798.