Browsing by Subject "Rare diseases"

Now showing 1 - 6 of 6
  • Thumbnail Image
    Item
    Creating a multi-center rare disease consortium - the Consortium of Eosinophilic Gastrointestinal Disease Researchers (CEGIR)
    (IOS Press, 2017-12-18) Cheng, Katherine; Gupta, Sandeep K.; Kantor, Susanna; Kuhl, Jonathan T.; Aceves, Seema S.; Bonis, Peter A.; Capocelli, Kelley E.; Carpenter, Christina; Chehade, Mirna; Collins, Margaret H.; Dellon, Evan S.; Falk, Gary W.; Gopal-Srivastava, Rashmi; Gonsalves, Nirmala; Hirano, Ikuo; King, Eileen C.; Leung, John; Krischer, Jeffrey P.; Mukkada, Vincent A.; Schoepfer, Alain; Spergel, Jonathan M.; Straumann, Alex; Yang, Guang-Yu; Furuta, Glenn T.; Rothenberg, Marc E.; Pediatrics, School of Medicine
    Eosinophilic gastrointestinal disorders (EGIDs) affect various segments of the gastrointestinal tract. Since these disorders are rare, collaboration is essential to enroll subjects in clinical studies and study the broader population. The Rare Diseases Clinical Research Network (RDCRN), a program of the National Center for Advancing Translational Sciences (NCATS), funded the Consortium of Eosinophilic Gastrointestinal Disease Researchers (CEGIR) in 2014 to advance the field of EGIDs. CEGIR facilitates collaboration among various centers, subspecialties, patients, professional organizations and patient-advocacy groups and includes 14 clinical sites. It has successfully initiated two large multi-center clinical studies looking to refine EGID diagnoses and management. Several pilot studies are underway that focus on various aspects of EGIDs including novel therapeutic interventions, diagnostic and monitoring methods, and the role of the microbiome in pathogenesis. CEGIR currently nurtures five physician-scholars through a career training development program and has published more than 40 manuscripts since its inception. This review focuses on CEGIR's operating model and progress and how it facilitates a framework for exchange of ideas and stimulates research and innovation. This consortium provides a model for progress on other potential clinical areas.
  • Thumbnail Image
    Item
  • Thumbnail Image
    Item
    Human and Machine Intelligence Together Drive Drug Repurposing in Rare Diseases
    (Frontiers Media, 2021-07-28) Challa, Anup P.; Zaleski, Nicole M.; Jerome, Rebecca N.; Lavieri, Robert R.; Shirey-Rice, Jana K.; Barnado, April; Lindsell, Christopher J.; Aronoff, David M.; Crofford, Leslie J.; Harris, Raymond C.; Ikizler, T. Alp; Mayer, Ingrid A.; Holroyd, Kenneth J.; Pulley, Jill M.; Medicine, School of Medicine
    Repurposing is an increasingly attractive method within the field of drug development for its efficiency at identifying new therapeutic opportunities among approved drugs at greatly reduced cost and time of more traditional methods. Repurposing has generated significant interest in the realm of rare disease treatment as an innovative strategy for finding ways to manage these complex conditions. The selection of which agents should be tested in which conditions is currently informed by both human and machine discovery, yet the appropriate balance between these approaches, including the role of artificial intelligence (AI), remains a significant topic of discussion in drug discovery for rare diseases and other conditions. Our drug repurposing team at Vanderbilt University Medical Center synergizes machine learning techniques like phenome-wide association study-a powerful regression method for generating hypotheses about new indications for an approved drug-with the knowledge and creativity of scientific, legal, and clinical domain experts. While our computational approaches generate drug repurposing hits with a high probability of success in a clinical trial, human knowledge remains essential for the hypothesis creation, interpretation, "go-no go" decisions with which machines continue to struggle. Here, we reflect on our experience synergizing AI and human knowledge toward realizable patient outcomes, providing case studies from our portfolio that inform how we balance human knowledge and machine intelligence for drug repurposing in rare disease.
  • Thumbnail Image
    Item
    Rare Disease, Advocacy and Justice: Intersecting Disparities in Research and Clinical Care
    (Taylor & Francis, 2023) Halley, Meghan C.; Halverson, Colin M. E.; Tabor, Holly K.; Goldenberg, Aaron J.; Medicine, School of Medicine
    Rare genetic diseases collectively impact millions of individuals in the United States. These patients and their families share many challenges including delayed diagnosis, lack of knowledgeable providers, and limited economic incentives to develop new therapies for small patient groups. As such, rare disease patients and families often must rely on advocacy, including both self-advocacy to access clinical care and public advocacy to advance research. However, these demands raise serious concerns for equity, as both care and research for a given disease can depend on the education, financial resources, and social capital available to the patients in a given community. In this article, we utilize three case examples to illustrate ethical challenges at the intersection of rare diseases, advocacy and justice, including how reliance on advocacy in rare disease may drive unintended consequences for equity. We conclude with a discussion of opportunities for diverse stakeholders to begin to address these challenges.
  • Thumbnail Image
    Item
    The Human Phenotype Ontology in 2024: phenotypes around the world
    (Oxford University Press, 2024) Gargano, Michael A.; Matentzoglu, Nicolas; Coleman, Ben; Addo-Lartey, Eunice B.; Anagnostopoulos, Anna V.; Anderton, Joel; Avillach, Paul; Bagley, Anita M.; Bakštein, Eduard; Balhoff, James P.; Baynam, Gareth; Bello, Susan M.; Berk, Michael; Bertram, Holli; Bishop, Somer; Blau, Hannah; Bodenstein, David F.; Botas, Pablo; Boztug, Kaan; Čady, Jolana; Callahan, Tiffany J.; Cameron, Rhiannon; Carbon, Seth J.; Castellanos, Francisco; Caufield, J. Harry; Chan, Lauren E.; Chute, Christopher G.; Cruz-Rojo, Jaime; Dahan-Oliel, Noémi; Davids, Jon R.; de Dieuleveult, Maud; de Souza, Vinicius; de Vries, Bert B. A.; de Vries, Esther; DePaulo, J. Raymond; Derfalvi, Beata; Dhombres, Ferdinand; Diaz-Byrd, Claudia; Dingemans, Alexander J. M.; Donadille, Bruno; Duyzend, Michael; Elfeky, Reem; Essaid, Shahim; Fabrizzi, Carolina; Fico, Giovanna; Firth, Helen V.; Freudenberg-Hua, Yun; Fullerton, Janice M.; Gabriel, Davera L.; Gilmour, Kimberly; Giordano, Jessica; Goes, Fernando S.; Gore Moses, Rachel; Green, Ian; Griese, Matthias; Groza, Tudor; Gu, Weihong; Guthrie, Julia; Gyori, Benjamin; Hamosh, Ada; Hanauer, Marc; Hanušová, Kateřina; He, Yongqun Oliver; Hegde, Harshad; Helbig, Ingo; Holasová, Kateřina; Hoyt, Charles Tapley; Huang, Shangzhi; Hurwitz, Eric; Jacobsen, Julius O. B.; Jiang, Xiaofeng; Joseph, Lisa; Keramatian, Kamyar; King, Bryan; Knoflach, Katrin; Koolen, David A.; Kraus, Megan L.; Kroll, Carlo; Kusters, Maaike; Ladewig, Markus S.; Lagorce, David; Lai, Meng-Chuan; Lapunzina, Pablo; Laraway, Bryan; Lewis-Smith, David; Li, Xiarong; Lucano, Caterina; Majd, Marzieh; Marazita, Mary L.; Martinez-Glez, Victor; McHenry, Toby H.; McInnis, Melvin G.; McMurry, Julie A.; Mihulová, Michaela; Millett, Caitlin E.; Mitchell, Philip B.; Moslerová, Veronika; Narutomi, Kenji; Nematollahi, Shahrzad; Nevado, Julian; Nierenberg, Andrew A.; Novák Čajbiková, Nikola; Nurnberger, John I., Jr.; Ogishima, Soichi; Olson, Daniel; Ortiz, Abigail; Pachajoa, Harry; Perez de Nanclares, Guiomar; Peters, Amy; Putman, Tim; Rapp, Christina K.; Rath, Ana; Reese, Justin; Rekerle, Lauren; Roberts, Angharad M.; Roy, Suzy; Sanders, Stephan J.; Schuetz, Catharina; Schulte, Eva C.; Schulze, Thomas G.; Schwarz, Martin; Scott, Katie; Seelow, Dominik; Seitz, Berthold; Shen, Yiping; Similuk, Morgan N.; Simon, Eric S.; Singh, Balwinder; Smedley, Damian; Smith, Cynthia L.; Smolinsky, Jake T.; Sperry, Sarah; Stafford, Elizabeth; Stefancsik, Ray; Steinhaus, Robin; Strawbridge, Rebecca; Sundaramurthi, Jagadish Chandrabose; Talapova, Polina; Tenorio Castano, Jair A.; Tesner, Pavel; Thomas, Rhys H.; Thurm, Audrey; Turnovec, Marek; van Gijn, Marielle E.; Vasilevsky, Nicole A.; Vlčková, Markéta; Walden, Anita; Wang, Kai; Wapner, Ron; Ware, James S.; Wiafe, Addo A.; Wiafe, Samuel A.; Wiggins, Lisa D.; Williams, Andrew E.; Wu, Chen; Wyrwoll, Margot J.; Xiong, Hui; Yalin, Nefize; Yamamoto, Yasunori; Yatham, Lakshmi N.; Yocum, Anastasia K.; Young, Allan H.; Yüksel, Zafer; Zandi, Peter P.; Zankl, Andreas; Zarante, Ignacio; Zvolský, Miroslav; Toro, Sabrina; Carmody, Leigh C.; Harris, Nomi L.; Munoz-Torres, Monica C.; Danis, Daniel; Mungall, Christopher J.; Köhler, Sebastian; Haendel, Melissa A.; Robinson, Peter N.; Psychiatry, School of Medicine
    The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs.
  • Thumbnail Image
    Item
    Use of funded multicenter prospective longitudinal databases to inform clinical trials in rare diseases-Examination of cholestatic liver disease in Alagille syndrome
    (Wolters Kluwer, 2022) Shneider, Benjamin L.; Kamath, Binita M.; Magee, John C.; Goodrich, Nathan P.; Loomes, Kathleen M.; Ye, Wen; Spino, Cathie; Alonso, Estella M.; Molleston, Jean P.; Bezerra, Jorge A.; Wang, Kasper S.; Karpen, Saul J.; Horslen, Simon P.; Guthery, Stephen L.; Rosenthal, Philip; Squires, Robert H.; Sokol, Ronald J.; Childhood Liver Disease Research Network (ChiLDReN); Pediatrics, School of Medicine
    The conduct of long-term conventional randomized clinical trials in rare diseases is very difficult, making evidenced-based drug development problematic. As a result, real-world data/evidence are being used more frequently to assess new therapeutic approaches in orphan diseases. In this investigation, inclusion and exclusion criteria from a published trial of maralixibat in Alagille syndrome (ALGS, ITCH NCT02057692) were applied to a prospective longitudinal cohort of children with cholestasis (LOGIC NCT00571272) to derive contextual comparator data for evolving clinical trials of intestinal bile acid transport inhibitors in ALGS. A natural history/clinical care cohort of 59 participants who met adapted inclusion and exclusion criteria of ITCH was identified from 252 LOGIC participants with ALGS with their native liver. Frequency weighting was used to match the age distribution of ITCH and yielded a cohort (Alagille Syndrome Natural History [ALGS NH]) that was very similar to the baseline status of ITCH participants. During a 2-year prospective follow-up there was a significant reduction in pruritus in the weighted ALGS NH cohort as assessed by the clinician scratch score (-1.43 [0.28] -1.99, -0.87; mean [SEM] 95% confidence interval). During the same time period, the total bilirubin, albumin, and alanine aminotransferase levels were unchanged, whereas platelet count dropped significantly (-65.2 [16.2] -98.3, -32.1). Weighted survival with native liver was 91% at 2 years in the ALGS NH. These investigations provide valuable real-world data that can serve as contextual comparators to current clinical trials, especially those without control populations, and highlight the value and importance of funded multicenter, prospective, natural history studies.