Undiagnosed diseases are likely to be determined by genetic, environmental, and developmental factors. While some undiagnosed diseases will represent novel rare genetic syndromes with monogenic or oligogenic etiologies and others will reflect rare manifestations of known diseases, many are likely to result from a more analytically challenging combination of multiple genetic, environmental, and developmental factors. Whole exome and whole genome sequencing are powerful tools with which to ascertain the genetic contributions to undiagnosed diseases; however, these methods alone are unlikely to elucidate the basis for many, if not most, undiagnosed diseases. The central unifying hypothesis of this proposal is, therefore, that an integrated, network-based, systems biology approach that incorporates not only genetic variation data, but also gene expression, metabolomic, proteomic, and exposomic data, along with careful deep phenotyping, will prove to be the most effective way to identify the pathways and mechanisms responsible for many undiagnosed diseases. To address the underlying hypothesis, we propose to establish an integrated interdisciplinary research plan for the Harvard Undiagnosed Disease Program Clinical Site (Harvard UDP-CS) that involves three specific aims: 1) ascertainment and clinical characterization - we will perform case ascertainment and phenotypic characterization for selected rare and undiagnosed disease states in adults and children; 2) genetic assessments - we will use patient and family member-derived DNA sequence, transcriptomic data (when available), and clinical phenotype information to identify potentially causal DNA sequence variants, gene expression variation, and potentially causative pathway derangements; and 3) network approach to disease diagnosis - we will integrate other -omic data, including metabolomic, proteomic, and exposomic data, along with the candidate genetic variants into the comprehensive interactome, and thereby identify diseases or disease pathways in network proximity to the involved genes that may help identify potential pathobiological modules relevant to the etiology of the undiagnosed disease. We will work toward meeting these specific aims and addressing the overall hypothesis in close collaboration with the coordinating center and other clinical sites in the UDN in order to develop and implement assessment protocols of phenotype, environment, and genotype that will ultimately define the etiology and treatment of undiagnosed diseases.

Public Health Relevance

This proposal describes our plan to develop a state-of-the-art strategy for evaluating patients with previously undiagnosed diseases. Clinical assessments will be combined with patient and family member genetic data, and environmental exposure data, within a framework that includes the NIH-sponsored and led undiagnosed diseases network and its consortium member sites.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project--Cooperative Agreements (U01)
Project #
3U01HG007690-04S1
Application #
9635044
Study Section
Special Emphasis Panel (ZHG1)
Program Officer
Wise, Anastasia Leigh
Project Start
2014-07-01
Project End
2018-08-31
Budget Start
2018-04-01
Budget End
2018-08-31
Support Year
4
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
030811269
City
Boston
State
MA
Country
United States
Zip Code
02115
Tao, Rongkun; Zhao, Yuzheng; Chu, Huanyu et al. (2017) Genetically encoded fluorescent sensors reveal dynamic regulation of NADPH metabolism. Nat Methods 14:720-728
Ramoni, Rachel B; Mulvihill, John J; Adams, David R et al. (2017) The Undiagnosed Diseases Network: Accelerating Discovery about Health and Disease. Am J Hum Genet 100:185-192
Handy, Diane E; Loscalzo, Joseph (2017) Responses to reductive stress in the cardiovascular system. Free Radic Biol Med 109:114-124
Shashi, Vandana; Pena, Loren D M; Kim, Katherine et al. (2017) De Novo Truncating Variants in ASXL2 Are Associated with a Unique and Recognizable Clinical Phenotype. Am J Hum Genet 100:179
Cassa, Christopher A; Smith, Stacy E; Docken, William et al. (2016) An argument for early genomic sequencing in atypical cases: a WISP3 variant leads to diagnosis of progressive pseudorheumatoid arthropathy of childhood. Rheumatology (Oxford) 55:586-9
Manrai, Arjun K; Funke, Birgit H; Rehm, Heidi L et al. (2016) Genetic Misdiagnoses and the Potential for Health Disparities. N Engl J Med 375:655-65
Loscalzo, Joseph (2016) Adaptions to Hypoxia and Redox Stress: Essential Concepts Confounded by Misleading Terminology. Circ Res 119:511-3
Ghiassian, Susan Dina; Menche, Jörg; Chasman, Daniel I et al. (2016) Endophenotype Network Models: Common Core of Complex Diseases. Sci Rep 6:27414
Krier, Joel B; Kalia, Sarah S; Green, Robert C (2016) Genomic sequencing in clinical practice: applications, challenges, and opportunities. Dialogues Clin Neurosci 18:299-312
Kitsak, Maksim; Sharma, Amitabh; Menche, Jörg et al. (2016) Tissue Specificity of Human Disease Module. Sci Rep 6:35241

Showing the most recent 10 out of 20 publications