New research offers hope for families living with genetics causes of kidney disease
Problems with the structure and formation of the organs that make up our urinary system (including the kidneys and bladder) are an important cause of kidney failure in children. Although some of the changes in genetic information that can cause these issues are now known, in many cases an answer cannot be found.
With support from Kidney Research UK and the Kids Kidney Research charity, Dr Mitra Kabir, Dr Kathryn Hentges and Professor Adrian Woolf from Manchester University have used a form of artificial intelligence known as machine learning to identify new genes that might be involved in kidney disease.
Supporting patients and families
Around half of all children receiving dialysis have kidney failure because of abnormalities in their urinary system that were present from birth. Scientific progress means that we can now identify the responsible genes in some but not all patients.
“Our genetics clinic in Manchester has worked with many patients over the last 12 years and we know that it is important for individuals with kidney problems to have a clear explanation of the causes. Currently we can identify a responsible gene in around 20% of cases, but for the remaining 80% we are often unable to determine the underlying reason. This can be distressing for the patient and their family and by gaining a greater understanding of the causes we may be better able to manage these conditions in future”. Professor Adrian Woolf
A new approach to finding previously unknown genes
The Manchester-based team, led by Dr Kathryn Hentges, used a technique called machine learning to identify trends and patterns in genes known to be linked to development of the urinary system. They then applied this technology to look at the genetic information from a mouse and find new genes that were likely to be involved in forming the kidneys and bladder. Their results showed that this technique can pinpoint new genes likely to be involved in kidney and bladder problems and could help scientists prioritise new targets for investigation.
“This new technology has the potential to help us find many previously missed genetic causes of kidney problems. We have already identified several new genes that had not been linked to renal problems before, and by making this tool available to other kidney researchers we hope to support many future breakthroughs in this area.” Dr Kathy Hentges
What is machine learning?
Machine learning is a type of artificial intelligence (computer-based problem solving) that provides answers or solutions based on previous knowledge or experience. Using this approach, a computer can answer a question based on what it has seen before. In this project, machine learning used existing knowledge of genes involved in bladder and kidney formation, which allowed the whole mouse genome to be checked for similar genes in an efficient and non-biased way.
Looking to the future
Although genetic testing is now available, the results are often slow, and many genes remain unknown. This new study offers a chance to identify many unknown disease-causing genes in a time-effective manner, providing answers for patients living with kidney disease. Further work will be needed to confirm the role of any newly found genes, with new research on a pioneering laboratory-based technique called organoids expected soon.
Read the full paper to find out more.
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