Center for Undiagnosed Diseases at Stanford

PROJECT SUMMARY The Center for Undiagnosed Diseases at Stanford, a member site of the Undiagnosed Diseases Network (UDN), works to improve the lives of patients with undiagnosed and rare diseases and their families. In a sustainable and inclusive manner, we offer cutting-edge diagnostic strategies and technologies to patients who continue a diagnostic odyssey after clinical options have been exhausted. In addition to pioneering innovative diagnostic methodology, we seek to deeply understand the needs and experience of the undiagnosed patient community to inform the design and implementation of best practices with regard to participant experience and the inclusion of underserved populations. The impacts of underinsurance and reduced access to subspecialty care and advanced diagnostics fall disproportionately on underserved populations, making it critical to build community partnerships in the conduct of rare disease studies. The Center for Undiagnosed Diseases (CUD) at Stanford will continue our efforts toward sustainability, refinement of methods, and collaboration with clinicians providing the standard of care. Here, we propose a program of study that will develop a deeper understanding of barriers to UDN enrollment faced by patients from underserved communities and implement mitigation strategies. To inform our work in studying barriers to participation and in building community partnerships, in Aim 1, we will establish an advisory board with representatives from the patient community as well as community health and social service providers. In Aim 2, we will work in collaboration with clinical partners in our region to identify, recruit, and diagnose a cohort of underserved, undiagnosed patients of diverse backgrounds, and empower community providers to participate in the UDN process through strategic partnering. In Aim 3, we will further enhance the diagnostic capabilities of the UDN by leveraging innovations in molecular diagnostics and advanced informatics. This work will include innovative approaches to transcriptomics, 2) long-read genome sequencing, 3) proteomics, and 4) the implementation of new strategies for the computational prioritization of candidate diagnosis and novel disease entities.