Tag: data sharing

searchMECFS: An online, interactive platform to facilitate secondary use of biospecimens and associated research data from myalgic encephalomyelitis studies

Abstract:

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex, debilitating disease affecting multiple body systems, with no established biomarkers for diagnosis or treatment. This publication introduces searchMECFS, a free, interactive online platform developed by the Data Management and Coordinating Center (DMCC) of the ME/CFS Research Network, with funding from the National Institutes of Health. The platform’s purpose is to facilitate the secondary use of biospecimens and associated research data from ME/CFS clinical studies by improving accessibility, visibility, and sharing of these resources.

Currently, searchMECFS facilitates access to biospecimens and associated data from two studies: The Chronic Fatigue Initiative (CFI) study funded by the Hutchins Family Foundation and the Multi-Site Clinical Assessment of ME/CFS study (MCAM) funded by the Centers for Disease Control and Prevention. Users can query participant demographics and clinical information and request available biospecimens through an application process. Eight specimen types are currently available, although availability varies by study.

The results highlight a case where a researcher used the searchMECFS platform to identify 40 serum samples, which contributed to published research on circadian rhythm disruption in ME/CFS. searchMECFS aims to accelerate scientific discovery within the ME/CFS research community by improving biospecimen utilization, fostering data sharing, and supporting collaboration.

Source: Barnette Q, LeGrow K, Ham M, Illei D, Giamberardino SN, Carnes MU, Brown LM. searchMECFS: An online, interactive platform to facilitate secondary use of biospecimens and associated research data from myalgic encephalomyelitis studies. Methods Rep RTI Press. 2026 Sep;2026. doi: 10.3768/rtipress.2026.mr.0058.2609. PMID: 42857848; PMCID: PMC13652500. https://pmc.ncbi.nlm.nih.gov/articles/PMC13652500/ (Full text)

mapMECFS: a portal to enhance data discovery across biological disciplines and collaborative sites

Abstract:

Background: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating disease which involves multiple body systems (e.g., immune, nervous, digestive, circulatory) and research domains (e.g., immunology, metabolomics, the gut microbiome, genomics, neurology). Despite several decades of research, there are no established ME/CFS biomarkers available to diagnose and treat ME/CFS. Sharing data and integrating findings across these domains is essential to advance understanding of this complex disease by revealing diagnostic biomarkers and facilitating discovery of novel effective therapies.

Methods: The National Institutes of Health funded the development of a data sharing portal to support collaborative efforts among an initial group of three funded research centers. This was subsequently expanded to include the global ME/CFS research community. Using the open-source comprehensive knowledge archive network (CKAN) framework as the base, the ME/CFS Data Management and Coordinating Center developed an online portal with metadata collection, smart search capabilities, and domain-agnostic data integration to support data findability and reusability while reducing the barriers to sustainable data sharing.

Results: We designed the mapMECFS data portal to facilitate data sharing and integration by allowing ME/CFS researchers to browse, share, compare, and download molecular datasets from within one data repository. At the time of publication, mapMECFS contains data curated from public data repositories, peer-reviewed publications, and current ME/CFS Research Network members.

Conclusions: mapMECFS is a disease-specific data portal to improve data sharing and collaboration among ME/CFS researchers around the world. mapMECFS is accessible to the broader research community with registration. Further development is ongoing to include novel systems biology and data integration methods.

Source: Mathur R, Carnes MU, Harding A, Moore A, Thomas I, Giarrocco A, Long M, Underwood M, Townsend C, Ruiz-Esparza R, Barnette Q, Brown LM, Schu M. mapMECFS: a portal to enhance data discovery across biological disciplines and collaborative sites. J Transl Med. 2021 Nov 8;19(1):461. doi: 10.1186/s12967-021-03127-3. PMID: 34749736. https://pubmed.ncbi.nlm.nih.gov/34749736/