An international team led by researchers at the MRC Epidemiology Unit has used a cross-platform approach across several large human studies to identify hundreds of novel genetic variants that regulate metabolite levels in the blood.
Human metabolism exchanges and converts small molecules, so called metabolites, to provide energy and essential components for each cell in the body or to excrete toxic by-products. The identification of variations in the genes that regulate these essential metabolic processes helps to better understand what causes common diseases and can lead to new strategies for their prevention and management.
In the present study published in Nature Genetics, an international team from the UK, Australia, USA, and Germany led by Dr Claudia Langenberg from the MRC Epidemiology Unit and the Berlin Institute of Health, Charité University Medicine Berlin, has identified hundreds of genetic variants not previously known to regulate blood metabolite levels in the population.
Dr Langenberg explains:
It is important to emphasize the potential clinical relevance of these findings. We see extraordinarily strong genetic effects on metabolite levels, more than three-fold compared to what we typically see for common genetic variants affecting body mass index or other complex traits, for example. We can attribute this to changes in the amino acid sequence of key metabolic ‘regulators’, such as enzymes and transporters.”
One example that demonstrates the translational potential of this work is the strong link between high levels of the amino acid serine and protection from a rare eye disease called macular telangiectasia type 2, highlighting new therapeutic opportunities. The authors showed in an independent study that the common genetic variants they identified for differences in plasma serine could distinguish between controls and patients with this severe and difficult to diagnose eye disease. In addition, the authors identify a novel mechanism by which impaired signaling through a receptor called GLP2R increases the risk of type 2 diabetes.
Dr Maik Pietzner, also at the MRC Epidemiology Unit and co-lead author of the study adds:
We hope these early, successful examples will encourage researchers and clinicians worldwide to test the relevance of our findings and the pathways we have uncovered for their disease of interest. All results are openly accessible to enable rapid follow-up via an interactive webserver www.omicscience.org.”
The team was able to achieve this largest study of this kind by being the first to integrate genetic association data for metabolites from over 85,000 individuals and demonstrating that results can successfully be combined across studies – including EPIC-Norfolk, Fenland and Interval – which use different metabolite measurement technologies.
- Lotta LA, Pietzner M, Stewart ID, Wittemans LBL, Li C, et al. A cross-platform approach identifies genetic regulators of human metabolism and health. Nature Genetics, 07 January 2021. DOI: 10.1038/s41588-020-00751-5
- Omicscience open access platform: https://omicscience.org/apps/crossplatform/