How susceptible are we to certain diseases and how severe will they be? The answer to this question fundamentally depends on our individual chemical fingerprint. It is made up of many small molecules in our blood, including fats, sugars and proteins. A study has now revealed numerous regions in the genome that shape our chemical fingerprint and influence how our body deals with external influences. The results provide a more detailed understanding of how diseases develop and may allow predictions about which people are affected well or less well by certain drugs.
Our metabolism is influenced by a number of internal and external factors: How do we eat, what diseases do we have, what medicines do we take and how much do we exercise? All of this contributes to how high our blood sugar and blood fat levels are, and what proteins are in the blood, for example to fight disease or to transmit hormone signals. Our genetic makeup also plays an important role. How exactly it affects our metabolism, however, has barely been explored until now.
A large population study
A team led by Praveen Surendran from the University of Cambridge in the UK has now investigated which regions of the genome are involved in shaping our individual chemical fingerprint. To do this, the researchers evaluated blood samples from nearly 20,000 people from two large population-based studies. They determined the levels of sugar, fats, hormones and other proteins in the blood and linked these results to variations in the genome of the test subjects.
“With our study, we are finally getting to the bottom of the genetic control of our metabolism through many hundreds of small metabolic products,” says co-author Claudia Langenberg from Charité-Universitätsmedizin Berlin. “As a result, we now understand what effects these genetic differences have on the development of a wide range of diseases and why.” In total, the researchers included more than 900 metabolic products in their analysis and discovered 330 regions in the genome in which rare or common variants affect the level of these metabolic products in the blood. “These metabolic ‘hotspots’ in the genome have helped us better understand which genes are actually relevant to the altered amounts of molecules in the blood,” says Langenberg.
Genes, metabolism and diseases
Researchers have identified numerous examples of how changes in metabolism affect the risk and progression of certain diseases. For example, if there is an increased concentration of the amino acid homoarginine in the blood, the risk of chronic kidney failure increases. Homoarginine is currently being tested as a means of preventing cardiovascular disease. “Our result underscores the need to carefully monitor renal function when administering homoarginine,” said Surendran and his team.
The results also show that metabolism not only contributes to maintaining health or causes disease, but that it also significantly determines how effective or sometimes harmful drugs are. For example, in about a fifth of the subjects, the research team found genetic changes near a gene important for breaking down some cancer drugs. In patients with the corresponding variation near this gene, the toxic substance breaks down more slowly, so it can build up in the blood and cause serious side effects. “Variants near genes that are also drug targets can give us clues about possible unwanted side effects,” explains Langenberg. From the authors’ point of view, the approach of identifying potential side effects at an early stage using genomic data could represent a rapid and cost-effective way to prioritize and avoid errors in future randomized trials.
Streamline your studies
The data in the current study come from people of European descent. To learn more about the links between genes, metabolism and health, the researchers want to conduct further studies in other populations. “We need larger studies that better map the genetic diversity of different population groups to understand the biological and clinical impact of genetic variations that differ between certain population groups,” says Langenberg.
Quelle: Praveen Surendran (University of Cambridge, UK) et al., Nature Medicine, doi: 10.1038/s41591-022-02046-0;