Insulin-dependent diabetes (type I) occurs after a subtle imbalance in the immune system, a colossal big data study has revealed.
In recent years, scientists all over the world have collected large quantities of genetic data, but analysing this ‘big data’ is a huge challenge. An international group of researchers headed by scientists from the University Medical Center Groningen (UMCG) have now succeeded. By analysing large quantities of data on genes and gene expression with new technologies, for about a hundred different diseases they could work out which processes become imbalanced in the body, even before people actually get sick.
The researchers investigated the DNA of 8,000 people and studied the consequences of DNA mutations. ‘We discovered that for many diseases the mutations all disrupted a single biological process’, says Dr Lude Franke, the main researcher on the project. This was completely unknown for many of these diseases. Franke gives the example of how insulin-dependent diabetes (type I diabetes) occurs. ‘We discovered that a mutation is responsible for a certain immune reaction becoming too extreme. This then functions as a “trigger” thus disrupting a process and leading to illness.’ Franke hopes that the new insights will contribute to the development of new drugs for diabetes, directed towards inhibiting this immune response.
According to Franke, this heralds a new phase in genetic research. ‘Researchers are traditionally inclined to formulate a single specific research question, gather data and then come to a conclusion. However, with the arrival of big data, better supercomputers and new mathematical techniques, it is now possible to conduct colossal studies that can provide the answers to a large number of different questions at the same time. This new approach has enabled us to acquire detailed insight into what exactly goes wrong in the body for a large number of different diseases, even before someone actually gets sick. This provides starting points for the development of drugs that correct these disrupted biological processes.’
The results of this research were published on 8 September 2013 in the renowned journal Nature Genetics.
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