The development of metabolic diseases like diabetes is a complex process. As well as lifestyle and environmental factors, many different genes are responsible for the pathogenesis of both type 1 and type 2 diabetes. These genes encode information on how to assemble individual proteins that function in glucose metabolism.
Many genes that play an important role in the development of human diseases are still unknown. It is only by deciphering the causal genetic links that we can understand diseases, develop therapeutic interventions, or even prevent an outbreak. Thus, the new diabetes genes discovered in this study could be used, for example, as biomarkers for individual risk prediction, early diagnosis of the disease, or personalised approaches for treatment.
Fifty-one new candidate genes for diabetes in humans
As part of the IMPC, knockout mice – each lacking a specific gene – were examined for metabolic dysfunction. Using this method, researchers are trying to establish whether the missing gene is involved in important metabolic processes and can be linked to human diseases.
"Our analysis of the phenotyping data has identified a total of 974 genes whose loss has strong effects on glucose and lipid metabolism," said Hrabě de Angelis, who led the study and is the Chair of Experimental Genetics at the Technical University of Munich. "For more than a third of the genes no connection to metabolism was known previously."
In addition, the researchers that teamed up with first author Dr. Jan Rozman, report that the functions of 51 of the discovered metabolic genes in the mouse were hitherto completely unknown. When compared with genome data collected in humans, they found that 23 genes appear to play a role in human diabetes. One of these genes is C4orf22, which appears to be involved in insulin action in participants of the diabetes study "Tübingen Family Study (TÜF)". This needs to be shown for the 51 new genes in the near future. They are new candidate genes, and mice that lack these genes may be important models to investigate impaired glucose metabolism and diabetes," explains Rozman, who coordinates the metabolic phenotyping at the German Mouse Clinic as part of the IMPC.
Interestingly, according to the bioinformatician and co-author Dr. Thomas Werner, these genes were also similar in their structure – many had common genetic elements. The scientists therefore assume that these genes belong to a network. In the future, they want to investigate these new regulatory structures and to explore to what extent they allow the prediction of gene functions of so-far unknown genes.