Article Text
Abstract
Background Clinical exome sequencing typically achieves diagnostic yields of 30%–57.5% in individuals with monogenic rare diseases. Undiagnosed diseases programmes implement strategies to improve diagnostic outcomes for these individuals.
Aim We share the lessons learnt from the first 3 years of the Undiagnosed Diseases Program-Victoria, an Australian programme embedded within a clinical genetics service in the state of Victoria with a focus on paediatric rare diseases.
Methods We enrolled families who remained without a diagnosis after clinical genomic (panel, exome or genome) sequencing between 2016 and 2018. We used family-based exome sequencing (family ES), family-based genome sequencing (family GS), RNA sequencing (RNA-seq) and high-resolution chromosomal microarray (CMA) with research-based analysis.
Results In 150 families, we achieved a diagnosis or strong candidate in 64 (42.7%) (37 in known genes with a consistent phenotype, 3 in known genes with a novel phenotype and 24 in novel disease genes). Fifty-four diagnoses or strong candidates were made by family ES, six by family GS with RNA-seq, two by high-resolution CMA and two by data reanalysis.
Conclusion We share our lessons learnt from the programme. Flexible implementation of multiple strategies allowed for scalability and response to the availability of new technologies. Broad implementation of family ES with research-based analysis showed promising yields post a negative clinical singleton ES. RNA-seq offered multiple benefits in family ES-negative populations. International data sharing strategies were critical in facilitating collaborations to establish novel disease–gene associations. Finally, the integrated approach of a multiskilled, multidisciplinary team was fundamental to having diverse perspectives and strategic decision-making.
- genomics
- genetics
- medical
- paediatrics
- genetic testing
- genetic techniques
Data availability statement
Data are available upon reasonable request.
Statistics from Altmetric.com
Data availability statement
Data are available upon reasonable request.
Footnotes
Twitter @LynnPais, @thorburn_mito
Contributors Data collection: TC, LG, NBT, AY, ZS, NJB, GM, MD, MGdS, LD, CSt, JE, SMW, TYT. Data analysis: TC, LG, LSP, NBT, AY, ZS, NJB, GM, MD, LD, CSt, AGC, AL, RO, DF, KMB, SS, SCL, GH, CSi, DM, DRT, AHO’D-L, JC, SMW, TYT. Research oversight, supervision and direction: DM, DRT, AHO’D-L, JC, SMW, TYT. Manuscript writing: TC, LG, SW, TYT. Data and manuscript review: all authors. TYT accepts responsibility as guarantor for the overall content of this manuscript.
Funding Funding for sequencing and analysis was provided by the National Human Genome Research Institute, the National Eye Institute, and the National Heart, Lung, and Blood Institute Center for Mendelian Genomics (grant UM1 HG008900) and by the National Human Genome Research Institute (grant R01 HG009141). We acknowledge financial support from the Murdoch Children’s Research Institute and the Harbig Foundation. Research conducted at the Murdoch Children’s Research Institute was supported by the Victorian Government’s Operational Infrastructure Support Program.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.