Latvian microbiome project draws attention

The Latvian Microbiome Project is a citizen science initiative aimed at establishing an overview of the microbiome of the Latvian population and how diet and lifestyle affect it. Launched in 2019, the project has so far involved 1000 voluntary participants and is almost ready for applying artificial intelligence (AI) tools to analyze the collected biospecimens and qualitative data. Participants will soon have access to Gut IT – a dedicated “health portal”, which will be updated as the pool of data grows. 

Jānis Kloviņš, lead researcher and head of the scientific council of the Latvian Biomedical Research and Study Centre and Laura Ansone, research assistant, spoke to Labs of Latvia on the goals of the initiative, findings so far and benefits for any individual who takes part. 

How did the idea of the Latvian Microbiome project arise and how do you plan to use the research?  

Kloviņš: The idea grew from trying to understand how the microbiome affects diseases and their treatment. The findings are multidimensional. We don’t just identify one bacterium and predict what will happen to a person. Microbiomes are complex compositions. So, we realised that we can only come to a result if we involve a sizeable amount of people. 

In this case we can’t apply the scheme used in clinical studies – splitting participants into groups according to their health to try to identify connections. Instead, we must look at the whole set of circumstances. Data collected from people in real time provides the best insight. At this point we have created the Latvian Microbiome reference database.

While we can’t promise to provide specific answers to questions, we are creating a participatory system, through which people can learn about themselves. In an ideal scenario, a person participates, they provide information on what they eat, their microbiome is analysed, and they receive the result. Should they decide to change something about their lifestyle, we can see any changes to the microbiome and make conclusions in real time if they choose to submit another sample. 

AI can help us find whatever it is that may be able to help transform something in people. Companies like DayTwo have an innovative approach. They build a personalised dietary plan for people based on the microbiome analysis. We’re not at that stage, but we’re heading there. 

We also gather a lot of information, which may be useful for entrepreneurs who can use our data or services to carry out targeted studies. As an example, someone might be developing a food product rich in prebiotics and wanting to study its effects. Our project has registered users who are happy to participate in research studies. We can offer them to take part voluntarily and the process can happen a lot faster than via the typical clinical research path. 

How do people find out about the Latvian Microbiome Project and how much interest has there been in participating? 

Ansone: We’re a scientific institution, so we don’t have a marketing department, but things happened quite fast with the help of posts on our institute’s Facebook page and a few interviews in which the project came up. Now, it’s come to word of mouth. Many participants recommend us to friends and family. We also have doctors on board who suggest the project to their patients because the results could be useful. 

Kloviņš: Compared to other projects, there has been more interest even though it costs EUR 30 to participate. Considering the scale of the project and that participants must register in the Genome Database of the Latvian population; we had some logistical hurdles to deal with. People must provide a blood sample, which requires visiting a clinic or, in times of Covid-19, arranging a home visit. The fee only covered the logistics and that is not sustainable. We’re thinking about introducing more convenient mechanisms, so that participants can prepare their own sample, send it by mail or courier. This could speed things up and boost our capacity. 

Ansone: People often call after hearing about the project and want to know what they will gain from participating. So, along with being a scientific study, this is also a matter of educating the public. 

What is the feedback from participants? 

Ansone: A lot of people, especially those who knew about the microbiome beforehand, like to compare their microbial diversity to the average. Many find peace in knowing that their diversity doesn’t differ from others’. 

Through speaking to participants, we learned that many of them have health issues and they’ve heard that the cause could stem from the microbiome. This is an opportunity to get an overview since no other microbiome tests are available in Latvia, just via foreign start-ups, which can be expensive. If something is wrong, the findings can encourage doing something about it. 

You mentioned that you collaborate with doctors. How have you involved medical practitioners in the project?  

Kloviņš: So far, we’ve collaborated with doctors who work in a similar field. This is largely not medicine of the “I’m sick and need to identify the cause” kind. We’re not aiming to answer this because we can’t make any promises. We provide information, which people and their doctors need to know how to use. One of the groups we work with is nutritionists who do their own research, have identified correlations, and can give recommendations based on the microbial diversity and species.  

Ansone: Usually, research draws on doctors from the relevant field, and they often receive some financial reward for onboarding patients. But, since this is a citizen science initiative and we are aware of how busy state-employed doctors are, we are collaborating with several private clinics and doctors. Involving the Anti-Aging Institute was a good step because the clinic itself is interested in offering its clients something innovative and previously unseen. In this case it’s not about making money because participants pay a fee. 

What’s next for the project? 

Kloviņš: Our next challenge is in the process of commercialisation. It’s very easy to sell something with an instant result, however, we don’t provide one. This is more of an investment in a person’s health. Once we have this data, it’s not going anywhere. 

To use AI, we need a large enough dataset, which represents a specific population, because microbiomes vary. Then we will be able to give more precise recommendations. So, we need people to take part now to be able to help them or others in future. 

The plan is to create services with a quicker turnaround time. This could be genetic information, which allows establishing a person’s polygenetic risk or how much they are at risk of certain diseases. Fundamentally, we’re talking about preventive medicine.  

Many people don’t believe that the data we’ve obtained so far is just the tip of the iceberg. What we’re working towards is the ability to determine pathogens. It will not be a diagnostic test but, if a person has issues and pathogenic bacteria could be to blame, this can motivate them to go get a real diagnostic test to confirm it and get the relevant treatment. 

Ansone: We use metagenomic sequencing, which differs from marker gene (typically 16S rRNA gene) sequencings in that it allows looking at all the genes in microbiota, not just distinct taxons. This has more value because, even if they are from the same species, bacteria can have different genomes and bacteria can exchange genes between them. So, by not looking at taxons, but genes, we can estimate their functions and the functions of the microbiota as a whole. For now, the reports that participants in our project receive are focused on taxons, but soon it looks like we will focus on genes and their functions. 

Kloviņš: This means people may have the exact same bacteria in their stomachs, because we, humans have named these bacteria and grouped them into species, however, bacteria compared to other organisms can effectively exchange genes. So, bacteria from one single species can differ greatly. A bacteria may not even differ but could have acquired a gene that produces something good or bad. One such example, which we might include in future reports, is gene resistance to antibiotics. Imagine, for example, that you find out that your bacteria contain tetracycline-resistant genes. In that case, if you are prescribed a tetracycline-based antibiotic, it may not perform as well. This cannot be determined with the 16S rRNA gene sequencing methodology currently in use around the world in similar projects (e.g., British Gut, American Gut).

How much of the information can you share? Have you established any trends so far? 

Ansone: We know that more women participate. Age-wise, we have everyone from kids to seniors, so the reference set is quite good. We’re yet to compile data on the bacteria. 

Kloviņš: When aggregated, the data is not secret because everyone has expressed their agreement to participate in the study. The data is anonymous, and we don’t publish individual microbiomes. 

We’re yet to find anything unusual. One of the pieces of information we provide is the most common bacteria in the human genome. We have come across some, which aren’t considered common in other publications. But databases are often updated, so we can’t say we’ve found something unique to Latvia because researchers from other countries might just be starting to investigate it. 

Do you share information with international colleagues? 

Kloviņš: If we felt like we could contribute something on a global level, we would. For now, the volume of what we’ve done can’t compare with the American Gut and British Gut projects.

Ansone: And they use different technology, so the research isn’t quite compatible. 

Kloviņš: From an ethics and open data perspective, it is standard to share anonymized data with the idea of helping scientists around the world to develop new methods and approaches. In theory, anyone has the right to forbid their data from being shared but then we can’t include them in the study. In terms of the biobank, if someone agrees to participate but doesn’t agree to certain aspects, then we don’t use their samples for that specific study. However, the whole idea of the project is that the data is open for the participant to gain the most.

Presumably, data privacy is one of the biggest concerns stopping people from participating.

Ansone: That’s also the educational part. When people phone, thinking this is a commercial service, we remind them that scientific research isn’t exactly a service, even though in this case the line is thin, since you pay to participate. 

Certain people are very afraid of sharing their data, so we explain the process of anonymization and what they stand to gain. Even if the person can’t feel the instant benefit, it is a benefit for the future of medicine. Any investment into preventive medicine will be smaller than what it will take to combat a disease once it has settled in. If we get the chance to explain that, the result is usually positive.  

Kloviņš: One way to explain is that we only start to see if a person is showing any risk of disease once we have established a cluster of samples. From there we can calculate risks of diabetes and other diseases. 

Source: labsoflatvia.com