In the world of rare disease, genomics has been transformational. Nobody sees this more clearly than Hywel Williams, manager of a translational genomics center at University College London’s Institute of Child Health that is dedicated to studying the genetic basis of uncharacterized and ultra-rare diseases in children.
Williams and his team work with clinicians whose patients are often the most hopeless of cases — they have usually been bounced around from one specialist to another on an unsuccessful diagnostic odyssey. The team uses Ingenuity Variant Analysis to find causal mutations in these children. In one new study just published in the American Journal of Human Genetics, they identified a novel syndrome that explained undiagnosed cases in three unrelated families.
The cases were brought to Williams’ center through Great Ormond Street Hospital, the largest pediatric research and clinical facility in Europe. The Centre for Translational Omics, more commonly known as GOSgene, functions in partnership with hospital clinicians. It was established by UCL professor Philip Beales and is funded by the hospital’s Biomedical Research Centre.
In the study, Williams and a crew of scientific and clinical experts identified a novel syndrome in three families. Each family had a previously undiagnosed disease thought to be unique; the identification of a syndrome linking these families’ conditions offers a promising research path for understanding the syndrome and diagnosing it in other affected individuals.
An integral part of that work was performed using Ingenuity Variant Analysis from QIAGEN Bioinformatics to make sense of the exome sequence data. GOSgene was an early adopter of the web-based application when it first came out in 2012 and has used it as a key component in its analysis pipeline ever since. In this case, the application directed Williams to a homozygous nonsense mutation in the SNX14 gene.
Ingenuity Variant Analysis is “essential to our analysis pipeline. All of our samples go into Variant Analysis,” Williams says. “It completely revolutionizes the way you can do gene identification.”