The future of medicine: How understanding our molecules can help treat diseases

Image credit: Nat Rev Rheumatol (2024). https://doi.org/10.1038/s41584-024-01208-3

Imagine if doctors could predict what diseases you might get, or know exactly which treatment would work best for you. That's the goal of personalized medicine, and new research is showing that we're getting closer to that reality. Scientists are now using powerful tools to look at our bodies on a molecular level to understand how diseases like arthritis and lupus work, and how to treat them more effectively. This involves studying things like our genes, proteins and immune cells.

One big idea is that many autoimmune diseases, where the body's defense system attacks itself, can be grouped together based on their molecular profiles, rather than just their traditional disease names. For instance, people with different autoimmune diseases might have similar patterns in their immune systems. This is like finding out that different types of cars actually have very similar engines. This means that treatments might be effective across multiple diseases that share these key features.

Using Big Data to Predict Disease

One way scientists are making progress is by using huge databases called biobanks, like the UK Biobank, which contains data from 500,000 people. These biobanks have a lot of information including:

1. Genetic data
2. Protein data
3. Metabolic data
4. Imaging data
5. Health records

With this data, scientists are using powerful computer programs to find patterns and predict who might develop a disease. One such program, called MILTON, can predict diseases by looking at specific molecular “signatures” in already diagnosed patients and then predicting potential new cases. This method can even predict diseases before they actually show up, and it works better than some existing risk scores. It can also improve predictions when combined with protein data. This is like having a crystal ball that can look at your molecules and tell you if you might get a disease in the future, before you even feel sick.

Looking at Shared Genes

Another approach is to study the genes of people with different autoimmune diseases, such as lupus, Sjögren's syndrome, and myositis. These diseases have overlapping symptoms, suggesting they might share some underlying causes. Researchers have found that specific genes, especially those in the major histocompatibility complex (MHC) region, play a big role in these diseases. These MHC genes are like the body's ID system, helping immune cells recognize "self" from "non-self".

However, it’s not just the common genetic variants that are important. Scientists are also looking at all genetic variations, including rare ones. This helps them see the bigger picture of how genes contribute to these diseases. For example, they discovered new genes related to the activation of the type I interferon pathway, which is known to be involved in many autoimmune conditions. They also found connections between certain autoantibodies, which are like mistaken identity tags in the body, and specific genes. One notable finding is that while some autoantibodies are linked to MHC region variants, others are linked to non-MHC genes, suggesting that environmental factors may also trigger the development of some autoimmune diseases.

Predicting Treatment Responses

It's not just about predicting disease, though. Scientists are also studying how people respond to treatments. One study looked at patients with inflammatory bowel disease (IBD) who were treated with a drug called infliximab. By looking at how the immune system changed over time, researchers identified patterns that predicted who would respond well to the drug and who would not. This approach uses something called a "disruption network" model, which shows how a treatment can change the way cells normally work, and it's helping scientists understand the best treatments for specific patients. Importantly, they found that the expression of certain genes at the baseline predicted treatment response, and these findings were validated in patients with rheumatoid arthritis. This kind of analysis could be used for better management of chronic diseases.

What's Next?

These studies show how analyzing molecular data can help us understand diseases in new ways, leading to better ways of predicting, diagnosing and treating illness. However, there are still some challenges such as validating findings in large groups of people and creating affordable tests. A key goal is to improve clinical trials, so that people are put in groups based on their molecular signatures. This could lead to treatments that are not only more effective but also more personalized.

In the future, doctors will be able to use these molecular profiles to choose the best treatment for each individual, rather than relying on a one-size-fits-all approach. This could also involve combining different types of data such as genes, proteins and immune cell types. This will lead to a new era of precision medicine, where treatments are tailored to the individual, leading to better outcomes and a healthier future.

Additional information: Nat Rev Rheumatol (2024). https://doi.org/10.1038/s41584-024-01208-3

Journal Information: https://www.nature.com/nrrheum/