Approved Research

The contribution of proteomics to multi-morbidity.

Lay summary

As medicine advances, the entire population is growing older, particularly in nations such as the UK. Unfortunately, this aging population is resulting in more people being diagnosed with multiple diseases - named multimorbidity; affecting over half of the over 65's in the UK (based on 2015 data). There are many consequences of multimorbidity, not only can it reduce life expectancy and cause debilitating symptoms, but it usually results in an individual taking many medications - which can cause other consequences in itself.

Some clusters of diseases tend to be more present in patients that others, for example, if you are diagnosed with type 2 diabetes, you may be more likely to have an osteoarthritis, hypertension or sleep apnoea diagnosis also. Although the reason for these clusters are often not well understood, they usually share common risk factors, for example, an individual that smokes, has a higher BMI and doesn't exercise will be at a higher risk of these diseases than others.

Proteins are complex substances our body rely on in order to function, these can usually be found travelling in the blood. People will naturally have higher or lower of levels of proteins, which is influenced by someone's genetics, or environmental factors such as diet. However, these differing levels can also result in a higher or lower risk of developing certain diseases.

In this project, I aim to identify proteins where having a naturally-occurring higher or lower level can causally contribute to the risk of both type 2 diabetes and osteoarthritis (a commonly occurring pair of diseases). With the information gathered, I aim to find new potential medications that will target both diseases, in turn, reducing the risk that comes with taking many medications. The methods used will also be repeated in other common pairs of diseases.