Data barriers limit genetic diagnosis
Original story at Nature News & Comment• 5 mentions • 1 year ago
Nature News & Comment 1 year ago
For the first five months of Harrison Harkins’ life, doctors had little idea about what was causing his spinal malformation and inability to gain weight. But in November 2011, Matthew Bainbridge, a computational biologist at Baylor College of Medicine in Houston, Texas, found a clue. After analysing genetic data from Harrison and his parents, Bainbridge discovered that the child had an abnormal version of a gene called ASXL3.But Bainbridge had no easy access to records of other children with ASXL3 mutations, and could not be sure that this mutation was the culprit. So he did what many scientists do: he networked. A Dutch team put Bainbridge in touch with German researchers who were treating another boy with an ASXL3 mutation — and symptoms similar to Harrison’s. After finding two further cases in an internal Baylor database, Bainbridge felt that the connection was concrete. He describes the syndrome seen in all four children, and probably caused by ASXL3 mutations, in a paper published on 5 February (M. N. Bainbridge et al. Genome Med. 5, 11; 2013).Researchers are using new tools to increase the pace of discoveries such as Bainbridge’s. Efforts to connect sequences with symptoms — or in genetic parlance, genotype with phenotype — have taken on increased urgency as clinical sequencing gains traction and funders put more money towards rare diseases. Researchers are planning to address the barriers to data sharing at a workshop in April, after the first International Rare Diseases Research Consortium Conference in Dublin. “There is a very positive feeling in the community that things are changing for the better,” says Peter Robinson, a computational biologist at the Charity University Hospital in Berlin.