Center for Undiagnosed Diseases at Stanford

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PROJECT SUMMARY The Center for Undiagnosed Diseases at Stanford, a member site of the Undiagnosed Diseases Network, works to improve the lives of patients with undiagnosed and rare diseases and their families. The Center is focused on the efficient and sustainable implementation of cutting-edge methods for diagnosis. We pioneer the use of new molecular diagnostics and analytic strategies to investigate the most challenging cases. In parallel with pursuing diagnostic advances, we seek to more deeply understand the needs and experience of the undiagnosed patient community to inform the implementation of best practices concerning participant experience and the inclusion of historically underserved populations. The impacts of underinsurance and reduced access to subspecialty care and advanced diagnostics fall disproportionately on underserved populations, making it critical to undertake outreach in rare disease studies. The Center for Undiagnosed Diseases (CUD) at Stanford will continue our efforts toward sustainability, refinement of methods, and integration with clinical practice. Here, we propose a program of study that will (1) facilitate accurate diagnosis of patients with undiagnosed diseases, with emphasis on those without or with limited insurance, economic or language barriers; (2) use novel approaches in data analysis and integration of different ‘omes to improve diagnostic rates; and (3) enhance our understanding of the impact of diversity on the diagnostic process. In Aim 1, we focus on enhancing the recruitment of diverse participants we propose to enroll and evaluate a new cohort of patients. This will include phenotypic assessment and biosample collection to facilitate genomic, multi-omic, and cellular disease evaluation. We are expanding our local patient advocacy partnerships, including a local UDN PEER group. In Aim 2, we advance methods and technologies to enhance diagnostic yield that have not yet crossed the translational divide. We leverage transcriptomics, metabolomics, long read sequencing, and immunomics to uncover diagnoses and mechanisms in undiagnosed participants. We apply novel computational approaches for systematic integration of multiomic and phenotypic data with the entire medical literature to improve diagnostic yield. In Aim 3, we focus on sustainability by promoting regional partnerships to promote the participation of historically underserved populations in the study. This work will encompass expanded outreach and education. We additionally will systematically investigate participant experience encompassing patient-reported outcomes to best understand the value of the Network to the patient community. This work will inform our practices and contribute to the evidence base necessary to support continued and expanded stakeholder investment in the UDN.