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What is multi-omics?

Let’s dive deeper into the world of multi-omics together with Jennifer Kirwan, Head of the Berlin Institute of Health Metabolomics Platform within Charite (with acknowledgements to Russell Hodge for his significant support in English language editing).

Multi-omics has become a buzzword in science, and taking the term apart will help explain what it means. The term „Omics“ refers to technologies that can capture a lot of the same type of measurements all at the same time. Genomic technologies, for example, report all of the genes in a cell or organism. Proteomics captures the proteins, and metabolomics measures the small molecules (metabolites) produced by biochemical reactions. And if you want to catalogue every microbe living in or on a human or another organism, you measure the microbiome.


Challenges of data interpretation

All omic studies have one thing in common: they produce huge amounts of data. But collecting data alone is not enough – it has to be interpreted, to understand what it actually means. And that can be really difficult when your data reveals a constantly changing landscape of hundreds of thousands of genes, proteins or metabolites. The aim is usually to zoom in on some process in an organism, such as the development of a disease; but which components are really essential? Which are causes, which are attempts at a solution, and which are just random noise? Added to that, some may simply be "false discoveries:“ if you were to repeat an experiment under slightly different conditions, you wouldn’t get the same result.

The power of multi-omics

One way to sort through all of the data and find something really significant is to put different technologies together and perform multi-omics! Here two or more omics datasets are put together to find connections between the changes happening in a cell or organism. This not only helps demonstrate that particular phenomena are real – it can also reveal new ones. Suppose, for example, we combined proteomics, metabolomics and microbiomic datasets from a population from Berlin. We might find that an increase in protein X in some people is associated with a decrease in metabolite Y, and both are connected to higher levels of a common human gut bacteria that raises the risk that people will develop a disease.

Uncovering biological significance

Multiomics are good at finding associations between factors like these. They can also do more, and suggest the fundamental biological mechanisms that connect them. In the case above, scientists might find that an increase in a protein can block an important metabolic process, which promotes the growth of a microbe, which triggers an immune response that damages the heart or lungs. Seeing the connection can lead to a hypothesis that can be tested in follow-up experiments. The end result may be new treatments, including targeting specific species of microbes that affect a person's chance of developing specific diseases. That would be an example of "precision medicine," targeted to a particular individual's biology!

Precision medicine and targeted treatments

Currently metabolomics, proteomics and clinical data are being combined in multi-omics approaches to explain a wide range of problems. Why, for example, do people with schizophrenia seem to age faster than the normal population? Surprisingly, it looks as if patients have some unusual inflammatory responses that might play a role(1). Another case involving the immune system involves the severity of Covid 19. This finding has come from linking metabolomics data to microbiome data. There seems to be a role for a type of gut bacteria (Clostridiales), and metabolic breakdown products of the amino acid tryptophan. Some of these products, such as kynurenine, are known to influence the immune system. Low levels of Clostridiales in the gut appeared to reduce other products, such as 5HT, in a way that influences how severe the disease becomes. This might occur because they reduce levels of a signalling chemical called IL6, which would otherwise ramp up the immune system's response in the early stage of infection(2).

Applications of multi-omics in research

So multi-omics approaches combine the power of diverse „omic“ technologies, exposing different aspects of organisms and suggesting links between different layers of biology. The associations and mechanisms they reveal deepen our understanding of disease processes. We are currently leveraging these tools within IMMEDIATE, where we will apply multi-omics techniques to investigate mechanisms of inflammation and how they contribute to a wide range of diseases. In addition, we will study whether adding "good bacteria" to patients' microbiomes could influence inflammations in a positive way.

  1. Campeau, A., Mills, R.H., Stevens, T. et al. Multi-omics of human plasma reveals molecular features of dysregulated inflammation and accelerated aging in schizophrenia. Mol Psychiatry 27, 1217–1225 (2022).
  2. Opitz, B., Essex, M., Pascual-Leone, B. M., Loeber, U., Kuhring, M., Zhang, B., ... & Forslund, S. (2023). Gut microbiota dysbiosis is associated with altered tryptophan metabolism and dysregulated inflammatory response in severe COVID-19.