Gastrointestinal and genitourinary symptoms in facioscapulohumeral muscular dystrophy: Prevalence and impact.

INTRODUCTION/AIMS: Anecdotally, patients with facioscapulohumeral muscular dystrophy (FSHD) describe gastrointestinal (GI) and genitourinary (GU) symptoms. We explored the prevalence of GI and GU symptoms and their impact on quality of life (QOL) in people with FSHD compared to healthy household controls. METHODS: In this descriptive, cross-sectional study, we emailed a survey exploring GI and GU symptoms to all FSHD Society patient contacts (n = 3507). We invited those with FSHD and unaffected household controls to respond. Non-parametric statistics were used to compare symptom frequency and impact of symptoms between respondents with FSHD and household controls. Within the FSHD group, symptom frequency was assessed relative to measures of disease progression (need for ambulatory or respiratory support). RESULTS: Surveys from 701 respondents (652 with FSHD) ≥18 years old were included in analysis. Those with FSHD had symptoms affecting both GI and GU systems more frequently than controls using ordinal rating of symptom frequency. Within the FSHD group, more advanced disease was associated with increased symptom frequency. QOL was negatively impacted by the GI and GU symptoms. There was no difference between groups in use of medications to treat these symptoms. DISCUSSION: Recognition and treatment of GI and GU symptoms in people with FSHD, particularly those with more advanced disease, could improve QOL. Additional investigation is required to confirm these findings and understand the physiology.

Meeting report: the 2021 FSHD International Research Congress.

Facioscapulohumeral muscular dystrophy (FSHD) is the second most common genetic myopathy, characterized by slowly progressing and highly heterogeneous muscle wasting with a typical onset in the late teens/early adulthood [1]. Although the etiology of the disease for both FSHD type 1 and type 2 has been attributed to gain-of-toxic function stemming from aberrant DUX4 expression, the exact pathogenic mechanisms involved in muscle wasting have yet to be elucidated [2-4]. The 2021 FSHD International Research Congress, held virtually on June 24-25, convened over 350 researchers and clinicians to share the most recent advances in the understanding of the disease mechanism, discuss the proliferation of interventional strategies and refinement of clinical outcome measures, including results from the ReDUX4 trial, a phase 2b clinical trial of losmapimod in FSHD [NCT04003974].

The Italian National Registry for FSHD: an enhanced data integration and an analytics framework towards Smart Health Care and Precision Medicine for a rare disease.

BACKGROUND: The Italian Clinical network for FSHD (ICNF) has established the Italian National Registry for FSHD (INRF), collecting data from patients affected by Facioscapulohumeral dystrophy (FSHD) and their relatives. The INRF has gathered data from molecular analysis, clinical evaluation, anamnestic information, and family history from more than 3500 participants. METHODS: A data management framework, called Mediator Environment for Multiple Information Sources (MOMIS) FSHD Web Platform, has been developed to provide charts, maps and search tools customized for specific needs. Patients' samples and their clinical information derives from the Italian Clinical network for FSHD (ICNF), a consortium consisting of fourteen neuromuscular clinics distributed across Italy. The tools used to collect, integrate, and visualize clinical, molecular and natural history information about patients affected by FSHD and their relatives are described. RESULTS: The INRF collected the molecular data regarding FSHD diagnosis conducted on 7197 subjects and identified 3362 individuals carrying a D4Z4 Reduced Allele (DRA): 1634 were unrelated index cases. In 1032 cases the molecular testing has been extended to 3747 relatives, 1728 carrying a DRA. Since 2009 molecular analysis has been accompanied by clinical evaluation based standardized evaluation protocols. In the period 2009-2020, 3577 clinical forms have been collected, 2059 follow the Comprehensive Clinical Evaluation form (CCEF). The integration of standardized clinical information and molecular data has made possible to demonstrate the wide phenotypic variability of FSHD. The MOMIS (Mediator Environment for Multiple Information Sources) data integration framework allowed performing genotype-phenotype correlation studies, and generated information of medical importance either for clinical practice or genetic counseling. CONCLUSION: The platform implemented for the FSHD Registry data collection based on OpenClinica meets the requirement to integrate patient/disease information, as well as the need to adapt dynamically to security and privacy concerns. Our results indicate that the quality of data collection in a multi-integrated approach is fundamental for clinical and epidemiological research in a rare disease and may have great value in allowing us to redefine diagnostic criteria and disease markers for FSHD. By extending the use of the MOMIS data integration framework to other countries and the longitudinal systematic collection of standardized clinical data will facilitate the understanding of disease natural history and offer valuable inputs towards trial readiness. This approach is of high significance to FSHD medical community and also to rare disease research in general.

The SWAN biomedical discourse ontology.

Developing cures for highly complex diseases, such as neurodegenerative disorders, requires extensive interdisciplinary collaboration and exchange of biomedical information in context. Our ability to exchange such information across sub-specialties today is limited by the current scientific knowledge ecosystem's inability to properly contextualize and integrate data and discourse in machine-interpretable form. This inherently limits the productivity of research and the progress toward cures for devastating diseases such as Alzheimer's and Parkinson's. SWAN (Semantic Web Applications in Neuromedicine) is an interdisciplinary project to develop a practical, common, semantically structured, framework for biomedical discourse initially applied, but not limited, to significant problems in Alzheimer Disease (AD) research. The SWAN ontology has been developed in the context of building a series of applications for biomedical researchers, as well as in extensive discussions and collaborations with the larger bio-ontologies community. In this paper, we present and discuss the SWAN ontology of biomedical discourse. We ground its development theoretically, present its design approach, explain its main classes and their application, and show its relationship to other ongoing activities in biomedicine and bio-ontologies.

Advancing translational research with the Semantic Web.

BACKGROUND: A fundamental goal of the U.S. National Institute of Health (NIH) "Roadmap" is to strengthen Translational Research, defined as the movement of discoveries in basic research to application at the clinical level. A significant barrier to translational research is the lack of uniformly structured data across related biomedical domains. The Semantic Web is an extension of the current Web that enables navigation and meaningful use of digital resources by automatic processes. It is based on common formats that support aggregation and integration of data drawn from diverse sources. A variety of technologies have been built on this foundation that, together, support identifying, representing, and reasoning across a wide range of biomedical data. The Semantic Web Health Care and Life Sciences Interest Group (HCLSIG), set up within the framework of the World Wide Web Consortium, was launched to explore the application of these technologies in a variety of areas. Subgroups focus on making biomedical data available in RDF, working with biomedical ontologies, prototyping clinical decision support systems, working on drug safety and efficacy communication, and supporting disease researchers navigating and annotating the large amount of potentially relevant literature. RESULTS: We present a scenario that shows the value of the information environment the Semantic Web can support for aiding neuroscience researchers. We then report on several projects by members of the HCLSIG, in the process illustrating the range of Semantic Web technologies that have applications in areas of biomedicine. CONCLUSION: Semantic Web technologies present both promise and challenges. Current tools and standards are already adequate to implement components of the bench-to-bedside vision. On the other hand, these technologies are young. Gaps in standards and implementations still exist and adoption is limited by typical problems with early technology, such as the need for a critical mass of practitioners and installed base, and growing pains as the technology is scaled up. Still, the potential of interoperable knowledge sources for biomedicine, at the scale of the World Wide Web, merits continued work.

AlzPharm: integration of neurodegeneration data using RDF.

BACKGROUND: Neuroscientists often need to access a wide range of data sets distributed over the Internet. These data sets, however, are typically neither integrated nor interoperable, resulting in a barrier to answering complex neuroscience research questions. Domain ontologies can enable the querying heterogeneous data sets, but they are not sufficient for neuroscience since the data of interest commonly span multiple research domains. To this end, e-Neuroscience seeks to provide an integrated platform for neuroscientists to discover new knowledge through seamless integration of the very diverse types of neuroscience data. Here we present a Semantic Web approach to building this e-Neuroscience framework by using the Resource Description Framework (RDF) and its vocabulary description language, RDF Schema (RDFS), as a standard data model to facilitate both representation and integration of the data. RESULTS: We have constructed a pilot ontology for BrainPharm (a subset of SenseLab) using RDFS and then converted a subset of the BrainPharm data into RDF according to the ontological structure. We have also integrated the converted BrainPharm data with existing RDF hypothesis and publication data from a pilot version of SWAN (Semantic Web Applications in Neuromedicine). Our implementation uses the RDF Data Model in Oracle Database 10g release 2 for data integration, query, and inference, while our Web interface allows users to query the data and retrieve the results in a convenient fashion. CONCLUSION: Accessing and integrating biomedical data which cuts across multiple disciplines will be increasingly indispensable and beneficial to neuroscience researchers. The Semantic Web approach we undertook has demonstrated a promising way to semantically integrate data sets created independently. It also shows how advanced queries and inferences can be performed over the integrated data, which are hard to achieve using traditional data integration approaches. Our pilot results suggest that our Semantic Web approach is suitable for realizing e-Neuroscience and generic enough to be applied in other biomedical fields.

Alzforum and SWAN: the present and future of scientific web communities.

Scientists drove the early development of the World Wide Web, primarily as a means for rapid communication, document sharing and data access. They have been far slower to adopt the web as a medium for building research communities. Yet, web-based communities hold great potential for accelerating the pace of scientific research. In this article, we will describe the 10-year experience of the Alzheimer Research Forum ('Alzforum'), a unique example of a thriving scientific web community, and explain the features that contributed to its success. We will then outline the SWAN (Semantic Web Applications in Neuromedicine) project, in which Alzforum curators are collaborating with informatics researchers to develop novel approaches that will enable communities to share richly contextualized information about scientific data, claims and hypotheses.

Alzforum.

The Alzheimer Research Forum Web site ( http://www.alzforum.org ) is an independent research project to develop an online community resource to manage scientific knowledge, information, and data about Alzheimer disease (AD). Its goals are to promote rapid communication, research efficiency, and collaborative, multidisciplinary interactions. Introducing new knowledge management approaches to AD research has a potentially large societal value. AD is among the leading causes of disability and death in older people. According to the Alzheimer's Association, four million Americans currently suffer from AD. That number is expected to escalate to over 10 million in coming decades. Patients progress from memory loss to a bedridden state over many years and require near-constant care. In addition to imposing a heavy burden on family caregivers and society at large, AD and related neurodegenerative disorders are among the most complex and challenging in biomedicine. Researchers have produced an abundance of data implicating diverse biological mechanisms. Important factors include genes, environmental risks, changes in cell functions, DNA damage, accumulation of misfolded proteins, cell death, immune responses, changes related to aging, and reduced regenerative capacity. Yet there is no agreement on the fundamental causes of AD. The situations regarding Parkinson, Huntington, and amyotrophic lateral sclerosis (ALS) are similar. The challenge of integrating so much data into testable hypotheses and unified concepts is formidable. What is more, basic understanding of these diseases needs to intersect with an equally complex universe of pharmacology, medicinal chemistry, animal studies, and clinical trials. In this chapter, we will describe the approaches developed by Alzforum to achieve knowledge integration through information technology and virtual community-building. We will also propose some future directions in the application of Web-based knowledge management systems in neuromedicine.

Barriers to drug discovery and development for Alzheimer disease.

Alzheimer disease (AD) is a neurodegenerative condition leading to progressive, irreversible loss of cognitive and behavioral function. Despite considerable investments in neuroscience research, only four drugs, all cholinesterase inhibitors, have been approved for the symptomatic management of AD in the United States. Although basically safe and modestly effective, these drugs are far from ideal, being neither universally efficacious nor disease modifying. AD exacts a considerable toll in direct medical costs, quality of life, and caregiver burden for persons and society. In addition to the obvious clinical benefit, therapeutic agents for AD and related dementias represent a considerable market opportunity for the pharmaceutical and biotechnology industries. There are currently 8-10 million AD sufferers in the seven major pharmaceutical markets. The market will grow rapidly in coming decades, as the developed world experiences an enormous increase in its elderly population. Given the great need for new therapeutic agents to manage and prevent AD, the Institute for the Study of Aging and the Fidelity Foundation organized a workshop, "Barriers to the Discovery and Development of Drugs for Alzheimer's Disease," to examine ways to expedite drug discovery and development. The identified barriers and potential solutions will be discussed here and in the accompanying articles in more detail.