There are few better examples of the need for data sharing than in the rare disease community, where patients, physicians, and researchers must search for “the needle in a haystack” to uncover rare, novel causes of disease within the genome. Impeding the pace of discovery has been the existence of many small siloed datasets within individual research or clinical laboratory databases and/or disease-specific organizations, hoping for serendipitous occasions when two distant investigators happen to learn they have a rare phenotype in common and can “match” these cases to build evidence for causality. However, serendipity has never proven to be a reliable or scalable approach in science. As such, the Matchmaker Exchange (MME) was launched to provide a robust and systematic approach to rare disease gene discovery through the creation of a federated network connecting databases of genotypes and rare phenotypes using a common application programming interface (API). The core building blocks of the MME have been defined and assembled. Three MME services have now been connected through the API and are available for community use. Additional databases that support internal matching are anticipated to join the MME network as it continues to grow.

Provision of a molecularly confirmed diagnosis in a timely manner for children and adults with rare genetic diseases shortens their "diagnostic odyssey," improves disease management, and fosters genetic counseling with respect to recurrence risks while assuring reproductive choices. In a general clinical genetics setting, the current diagnostic rate is approximately 50%, but for those who do not receive a molecular diagnosis after the initial genetics evaluation, that rate is much lower. Diagnostic success for these more challenging affected individuals depends to a large extent on progress in the discovery of genes associated with, and mechanisms underlying, rare diseases. Thus, continued research is required for moving toward a more complete catalog of disease-related genes and variants. The International Rare Diseases Research Consortium (IRDiRC) was established in 2011 to bring together researchers and organizations invested in rare disease research to develop a means of achieving molecular diagnosis for all rare diseases. Here, we review the current and future bottlenecks to gene discovery and suggest strategies for enabling progress in this regard. Each successful discovery will define potential diagnostic, preventive, and therapeutic opportunities for the corresponding rare disease, enabling precision medicine for this patient population.

The BRCA Challenge is a long-term data-sharing project initiated within the Global Alliance for Genomics and Health (GA4GH) to aggregate BRCA1 and BRCA2 data to support highly collaborative research activities. Its goal is to generate an informed and current understanding of the impact of genetic variation on cancer risk across the iconic cancer predisposition genes, BRCA1 and BRCA2. Initially, reported variants in BRCA1 and BRCA2 available from public databases were integrated into a single, newly created site, www.brcaexchange.org. The purpose of the BRCA Exchange is to provide the community with a reliable and easily accessible record of variants interpreted for a high-penetrance phenotype. More than 20,000 variants have been aggregated, three times the number found in the next-largest public database at the project’s outset, of which approximately 7,250 have expert classifications. The data set is based on shared information from existing clinical databases—Breast Cancer Information Core (BIC), ClinVar, and the Leiden Open Variation Database (LOVD)—as well as population databases, all linked to a single point of access. The BRCA Challenge has brought together the existing international Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium expert panel, along with expert clinicians, diagnosticians, researchers, and database providers, all with a common goal of advancing our understanding of BRCA1 and BRCA2 variation. Ongoing work includes direct contact with national centers with access to BRCA1 and BRCA2 diagnostic data to encourage data sharing, development of methods suitable for extraction of genetic variation at the level of individual laboratory reports, and engagement with participant communities to enable a more comprehensive understanding of the clinical significance of genetic variation in BRCA1 and BRCA2.

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Highlights PREVENT-AD is openly releasing datasets to the neuroscience community. PREVENT-AD is a longitudinal study of older adults at-risk of Alzheimer disease. Data include imaging, genetics, fluid biochemistry, neurosensory, cognition and more. Data collection methods and data sharing plans for open science are described.