4.5 Article

Lessons learnt from multifaceted diagnostic approaches to the first 150 families in Victoria's Undiagnosed Diseases Program

Journal

JOURNAL OF MEDICAL GENETICS
Volume 59, Issue 8, Pages 748-758

Publisher

BMJ PUBLISHING GROUP
DOI: 10.1136/jmedgenet-2021-107902

Keywords

genomics; genetics; medical; paediatrics; genetic testing; genetic techniques

Funding

  1. National Human Genome Research Institute [R01 HG009141]
  2. National Eye Institute
  3. National Heart, Lung, and Blood Institute Center for Mendelian Genomics [UM1 HG008900]
  4. Murdoch Children's Research Institute
  5. Harbig Foundation
  6. Victorian Government's Operational Infrastructure Support Program

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This study shared the lessons learned from the first three years of the Undiagnosed Diseases Program in Victoria, Australia, highlighting the importance of flexible implementation of multiple strategies, utilizing family-based exome sequencing, and international data sharing strategies to improve diagnostic outcomes for individuals with rare diseases.
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.

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