Congratulations to Dr Morris Swertz, who has been awarded an NWO-VIDI to develop “Scalable ‘big data’ methods towards personalized genome diagnostics”.
New NGS techniques can now measure all the DNA variations in an individual in one experiment. Unfortunately, this is not yet leading to more diagnoses bacause genetic labs are drowning in the amount of data produced. Previously, tests were performed only on single genes. This VIDI project will develop personalized whole genome diagnostics (patient-oriented techniques to find damaging mutations more quickly and better).
With the costs of next-generation sequencing dropping rapidly, we expect thousands of patients to soon have whole-genome profiling, and although NGS-based genetic testing is a major improvement over Sanger sequencing (one-gene-at-a-time), its implementation is a huge challenge for diagnostic laboratories. Analysis is still largely performed manually and can take months, while supporting software is based on simple filters and one-size-fits-all estimation tools, basically ignoring (public) big data. This means clinicians see thousands of DNA variants of unclear pathogenicity and the majority of patients remain without a clear diagnosis. The primary roadblock is not the data acquisition, but its interpretation.
Dr Swertz will develop novel methods to enable personalized whole-genome diagnostics. He has three objectives for his VIDI project:
(1) to develop new patient-centric methods including gene-specific models for classifying pathogenicity, RNA sequencing as a diagnostics tool, and a system for automated analysis/re-analysis of patients;
(2) to develop population-based ‘big data’ methods, producing knowledge on the functional effects of gene-damaging mutations, constrained and non-constrained genes, and developing disease-specific gene networks to prioritize DNA variants in genomic regions not yet diagnosed;
(3) to facilitate rapid translation from research to clinical practice by developing user-friendly and open source tools (co-financed by UMCG) with training materials and a readiness level that enables ‘self-service’.
He aims to publish 2-3 scientific papers per year.
He will develop these methods in close collaboration with diagnosticians and clinicians in order to validate the new methods immediately with real patient data. They wiill start with patients with cardiac phenotypes and then scale-up to other patient groups. With his background and expertise in: (1) DNA and RNA data analysis, (2) large-scale analysis methods, (3) user-friendly software for data interpretation, and (4) his collaborations with many clinicians, he is in a unique position to take these much-needed steps towards personalized whole-genome diagnostics.