Progress towards the discovery of the genetic basis of every rare disease has been substantial since the advent of whole exome and whole genome sequencing, yet there remain a nontrivial number of unsolved disorders and a molecular diagnosis remains elusive for a significant number of rare disease patients. The reasons that such discovery and diagnostic efforts fail are myriad and most likely include both technical limitations and disease mechanisms that are beyond our current technological abilities. These mechanisms possibly include genomic alterations, mutations affecting gene regulation (i.e., splicing and enhancers), mosaicism, and complex inheritance. To respond to this next level of complexity and address the undiagnosed and unsolved rare diseases, IRDiRC brought together a Task Force of world experts in each of these areas.
The IRDiRC Solving the Unsolved (STU) Task Force members gathered on March 25, 2018, at the Wellcome Genome Campus Conference Centre, Hinxton, UK, to formulate approaches to tackle this challenge. The day included presentations by each expert in which they described their mechanism of interest, proposed patient presentations for which the mechanism should be considered, and described approaches available to interrogate mutations. The group identified assets and gaps that respectively propel and hold back progress in the relevant research area, and put forward suggestions of next steps to enable diagnoses of diseases caused by this underlying mechanism. Additional discussions included the role of integrated ‘omics and novel computational approaches. Finally, the STU Task Force tried to develop a decision-tree for patients that remain unsolved following clinical exome sequencing.
A white paper is currently under development, which will lay out the state of play for rare disease discovery, the mechanisms explored during this workshop, and the research gaps to address by way of future funding calls. This Task Force aims to ultimately enable the timely molecular diagnosis of every patient, not just identify every disease-gene association.