Establishing The Australian Undiagnosed Disease Network (UDN-Aus); Australia’s first national rare disease diagnostic network

Technical Summary: Establishing The Australian Undiagnosed Disease Network (UDN-Aus)

Problem Statement
Rare diseases affect approximately 1 in 12 individuals globally, yet a significant proportion of patients with suspected monogenic conditions remain undiagnosed despite clinical genomic testing. In Australia, the diagnostic rate for suspected monogenic conditions plateaus at roughly 50%, leaving many families on a prolonged "diagnostic odyssey" involving costly, invasive, and fragmented investigations. Existing diagnostic pathways are hindered by siloed genomic data, jurisdictional funding disparities, variable access to testing across states, and a lack of standardized infrastructure for data transfer and reanalysis. Furthermore, priority populations—including Indigenous Australians, those from culturally and linguistically diverse (CALD) backgrounds, and rural/remote communities—face systemic barriers to equitable access. While state-based Undiagnosed Disease Programs (UDPs) exist in Australia, they suffer from inconsistent criteria, reliance on short-term grant cycles, and an inability to support national data sovereignty and sharing.

Methodology
The Australian Undiagnosed Disease Network (UDN-Aus) was established as a national collaborative initiative funded by the Medical Research Future Fund (MRFF) to create a standardized, equitable pathway for diagnosing undiagnosed rare diseases. The study was conducted across 12 clinical recruitment sites and 4 laboratory/research sites, coordinated by the Murdoch Children's Research Institute (MCRI).

• Governance and Structure: The network operates under a Multi-Institute Agreement (MIA) and is overseen by a National Steering Committee, a National Coordination Team, and specialized subcommittees: a Data Acquisition and Sharing Group (DASG), a Clinical Review/Multi-Disciplinary Team (MDT), and an Investigator Committee. Crucially, Community Advisory Groups (CAG) and an Indigenous Advisory Group (IAG) were embedded to ensure cultural safety, data sovereignty (particularly for Aboriginal and Torres Strait Islander participants), and alignment with community needs.
• Study Design and Recruitment: The study recruited genetically unsolved families referred by clinical genetics services. Inclusion criteria required a high likelihood of a monogenic cause, prior appropriate diagnostic testing (typically non-diagnostic exome sequencing), and the potential for a diagnosis to impact clinical management or reproductive counseling. A prioritization scoring system (out of 15 points) was applied to balance clinical need, scientific likelihood of a diagnosis, and equity factors (e.g., remote location, Indigenous status, low socioeconomic status).
• Data and Sample Workflow:
  1. Pre-enrolment: Clinicians identified potential candidates and obtained verbal consent to share de-identified data via a secure REDCap database.
  2. Genomic Reanalysis: Existing clinically generated genomic data (Exome or Whole Genome Sequencing) was transferred to the Centre for Population Genomics (CPG) for analysis on the seqr platform and the CaRDinal integrated analysis system.
  3. Advanced Testing: Cases without a diagnosis underwent expanded testing, including research trio sequencing, RNA-Seq, or long-read sequencing.
  4. Functional Analysis: Novel candidate variants were submitted to the Matchmaker Exchange. Functional investigations (e.g., proteomics) were conducted, with strict adherence to Indigenous data sovereignty principles prohibiting offshore testing for Indigenous participants.
  5. Workforce Development: The project included training workshops for clinicians on variant analysis using seqr, though operational reliance shifted toward dedicated variant curators due to time constraints.
• Ethics and Governance: The study navigated complex ethical approvals across 12 sites, requiring 11 amendments to the initial ethics application and extensive negotiation of Data Transfer Agreements (DTAs) and Research Collaboration Agreements (RCAs).

Key Contributions

• National Infrastructure: UDN-Aus established Australia's first national UDP, unifying previously fragmented state-based efforts into a cohesive network with standardized enrollment criteria and governance.
• Equitable Framework: The program operationalized principles of Indigenous data sovereignty and equity, ensuring that recruitment prioritized underrepresented populations and that data for Indigenous participants remained onshore.
• Technical Pipeline: The study validated a workflow for reanalyzing existing clinical genomic data and integrating it with frontier technologies (RNA-Seq, long-read sequencing, proteomics) within a national framework.
• Governance Models: The paper documents the specific administrative, legal, and ethical mechanisms required to establish a multi-institute national research network in Australia's federated health system, including the development of tailored consent forms and data transfer protocols.

Results

• Recruitment and Approval: The network successfully reviewed 250 families for enrollment across all Australian states and territories. Of these, 200 families were approved for enrollment, with research analysis and testing ongoing at the time of publication.
• Operational Metrics: The study conducted 64 national MDT meetings, 16 Investigator meetings, and numerous subcommittee meetings. It employed a national coordination team that expanded from 0.6 to 1.6 Full-Time Equivalent (FTE) to manage the administrative burden.
• Workforce Insights: While training workshops increased clinician confidence in using seqr, the study found that independent clinician-led variant curation was not sustainable due to time constraints. Consequently, the project relied heavily on dedicated variant curators (totaling ~3.0 FTE) to prevent bottlenecks.
• Barriers Identified: The most significant barrier to implementation was the time-intensive and variable nature of research governance approvals across sites (average 20.2 weeks, ranging up to 102 weeks). Negotiating Data Transfer Agreements with laboratories also proved challenging, taking an average of 22.25 weeks per agreement, and one private provider pathway failed to materialize.
• Financials: The study incurred significant costs related to ethics and governance applications ($5,329 AUD in direct fees, with an estimated $250,000 AUD in staff time dedicated to approvals).

Significance
The paper posits that UDN-Aus provides a "proof of concept" for a sustainable, national undiagnosed disease diagnostic pathway in Australia. Its significance lies not only in the potential for individual diagnoses but in its demonstration of the necessary components for national genomic research:

1. Standardization: It highlights the necessity of standardized referral criteria and governance structures to ensure equitable access across jurisdictions.
2. Community Engagement: It underscores that meaningful engagement with Indigenous and rare disease communities is not merely ethical but operational, influencing study design, consent, and data sovereignty policies.
3. Infrastructure Needs: The study argues that future success depends on systemic reforms, specifically the establishment of a national framework for genomic data governance and infrastructure to streamline data sharing, as current siloed approaches and manual transfer processes are inefficient and costly.
4. Workforce Reality: It identifies a critical gap in the clinical genomics workforce, noting that while upskilling is valuable, dedicated bioinformatic and variant curation resources are essential for the delivery of results in a national program.

The authors conclude that while UDN-Aus has established vital groundwork, the sustainable delivery of genomic research for rare disease in Australia requires continued investment in national data transfer policies, infrastructure, and research ethics procedures.