The case for open science: rare diseases.

The premise of Open Science is that research and medical management will progress faster if data and knowledge are openly shared. The value of Open Science is nowhere more important and appreciated than in the rare disease (RD) community. Research into RDs has been limited by insufficient patient data and resources, a paucity of trained disease experts, and lack of therapeutics, leading to long delays in diagnosis and treatment. These issues can be ameliorated by following the principles and practices of sharing that are intrinsic to Open Science. Here, we describe how the RD community has adopted the core pillars of Open Science, adding new initiatives to promote care and research for RD patients and, ultimately, for all of medicine. We also present recommendations that can advance Open Science more globally

Why MSM in rural South African communities should be an HIV prevention research priority.

Research into HIV and men who have sex with men's (MSM) health in South Africa has been largely confined to the metropolitan centres. Only two studies were located making reference to MSM in rural contexts or same-sex behaviors among men in the same. There is growing recognition in South Africa that MSM are not only disproportionately affected by HIV and have been underserved by the country's national response, but that they contribute significantly to sustaining the high number of new infections recorded each year. We argue that to meet the objectives of the country's national strategic plan for HIV, STI and TB it is important we know how these behaviours may be contributing to the sustained rural HIV epidemic in the youngest age groups and determine what constitutes appropriate and feasible programmatic response that can be implemented in the country's public sector health services

Expanding research to provide an evidence base for nutritional interventions for the management of inborn errors of metabolism

A trans-National Institutes of Health initiative, Nutrition and Dietary Supplement Interventions for Inborn Errors of Metabolism (NDSI-IEM), was launched in 2010 to identify gaps in knowledge regarding the safety and utility of nutritional interventions for the management of inborn errors of metabolism (IEM) that need to be filled with evidence-based research. IEM include inherited biochemical disorders in which specific enzyme defects interfere with the normal metabolism of exogenous (dietary) or endogenous protein, carbohydrate, or fat. For some of these IEM, effective management depends primarily on nutritional interventions. Further research is needed to demonstrate the impact of nutritional interventions on individual health outcomes and on the psychosocial issues identified by patients and their families. A series of meetings and discussions were convened to explore the current United States’ funding and regulatory infrastructure and the challenges to the conduct of research for nutritional interventions for the management of IEM. Although the research and regulatory infrastructure are well-established, a collaborative pathway that includes the professional and advocacy rare disease community and federal regulatory and research agencies will be needed to overcome current barriers

The collective impact of rare diseases in Western Australia: an estimate using a population-based cohort.

PURPOSE: It has been argued that rare diseases should be recognized as a public health priority. However, there is a shortage of epidemiological data describing the true burden of rare diseases. This study investigated hospital service use to provide a better understanding of the collective health and economic impacts of rare diseases. METHODS: Novel methodology was developed using a carefully constructed set of diagnostic codes, a selection of rare disease cohorts from hospital administrative data, and advanced data-linkage technologies. Outcomes included health-service use and hospital admission costs. RESULTS: In 2010, cohort members who were alive represented approximately 2.0% of the Western Australian population. The cohort accounted for 4.6% of people discharged from hospital and 9.9% of hospital discharges, and it had a greater average length of stay than the general population. The total cost of hospital discharges for the cohort represented 10.5% of 2010 state inpatient hospital costs. CONCLUSIONS: This population-based cohort study provides strong new evidence of a marked disparity between the proportion of the population with rare diseases and their combined health-system costs. The methodology will inform future rare-disease studies, and the evidence will guide government strategies for managing the service needs of people living with rare diseases.Genet Med advance online publication 22 September 2016Genetics in Medicine (2016); doi:10.1038/gim.2016.143

The GRDR-GUID: a model for global sharing of patients de-identified data

<p><strong>The GRDR-GUID: a model for global sharing of patients de-identified data</strong></p> <p><strong><em>Yaffa R. Rubinstein1; Matthew McAuliffe2; Manuel Posada3; Domenica Taruscio4; Stephen C. Groft1</em></strong></p> <p><em>1Office of Rare Disease Research/NCATS/NIH, 2Center for Information Technology/NIH, 3 Institute of Rare Diseases Research, IIER-ISCIII, 4National Centre for Rare Diseases, Istituto Superiore di Sanità (Rome, Italy)</em></p> <p>The Global Rare Diseases Patient Registry Data Repository-GRDR aggregates de-identified patient data, using CDEs, from various rare disease registries utilizing a Global Unique Identifier (GUID)(1). The GUID is a unique random alpha-numeric set of characters assignedto each patient-data that GUID is NOT directly generated from personally identifiable information (PII). The GUID system allows the patient to be followed across studies and registries can be used also to link to biospecimens.</p> <p>GUID Process</p> <p>User executes the GUID tool client locallyPII is enteredPII is combined and one-way hash codes are generatedThe one-way hash codes are sent to the GUID serverIf the hash codes match the server's hash codes for an existing GUID, then that GUID is returnedIf the hash codes do not match, then a new random GUID is generated and returned</p> <p>To generate a GUID for the subject, the following PII is required (these elements are included in the ORDR/GRDR list of CDEs) (PII is never sent to the GRDR system):</p> <p>Complete legal given (first) name of subject at birthComplete Legal additional name of subject at birth (if the subject has a middle name)Complete legal family (last) name of the subject at birthDay of birth (1-31)Month of birth (1-12)Year of birth (####)Name of city/municipality in which subject was bornCountry of birthPhysical sex of subject at birth (M/F)</p> <p>The GUID is an ID that allows researchers to share data specific to a study participant without exposing PII and to track participants longitudinally, across multiple research sites and across multiple studies. RD-CONNECT (IRDiRC framework) is assessing possibilities to implement a GUID strategy in their work and the NIH-GUID is one of the possibilities under consideration.</p> <p>(1) Johnson SB, Whitney G, McAuliffe M, etal. Using Global Unique Identifiers to Link Autism Collections. J. Am. Med. Inform. Assoc. July 17, 2010. 10.1136/jamia.2009.002063.</p