Genetic diagnosis of developmental disorders in the DDD study: a scalable analysis of genome-wide research data
4th April 2015
“The increasing use of whole exome and whole genome sequencing in both research and clinical practice raises questions about how to maximise the diagnostic usefulness of genomic data and how to share results with research participants and patients. Furthermore, it is increasingly deemed ethically desirable to return clinically useful results to research participants. However, return of individual genomic results poses major logistical challenges. A robust workflow must be developed to track individual samples and datasets, generate high-quality genomic data, filter out a very large number of probably benign variants, prioritise plausibly pathogenic variants, and link these findings to individual clinical data for interpretation and appropriate clinical follow-up. Health-related findings from a human genome could potentially include thousands of variants pertaining to hundreds of different conditions, almost none of which provide clinically useful information for a specific individual. A first step toward addressing these challenges is to separate potential genomic findings into those that are pertinent to a particular disease investigation and those that are non-pertinent (or incidental) to that disease. Although many commentators have debated the merits of returning different classes of findings from large research studies and biobanks, none has yet provided a scalable mplementation from patient identification through to a confirmed diagnosis within a research context. Here we describe the development and implementation of a translational genomics workflow in a large-scale rare disease research study to communicate pertinent findings to individual research participants, whilst minimising incidental findings…”
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Available at https://doi.org/10.1016/S0140-6736(14)61705-0