Active clinical trials for "Rare Diseases"

In the DISCO-TWIN study (prospective, open-label molecular-genetic study), twin pairs with one healthy and one affected twin with molecularly undiagnosed diseases will be analysed by means of omics technologies and/ or re-analysed using existing datasets. Phenotype and omics data will be shared within the University Hospital Tübingen and with external collaborators to improve the diagnostic rate of the subjects included in the study.

Most diagnostically unsolved rare disease have a genetic cause. These causes have not been found applying the current methodologies due to technical limitations (e.g. repeat expansions, changes in non-coding (intronic) regions) or, although methodically recorded, their pathophysiological significance but not classified as clinically relevant. A re- and meta-analysis of existing data sets with new algorithms and statistical models as well as the complementation with other omics technologies followed by functional follow-up studies in appropriate disease models (e.g. patient cell lines) allows to elucidate additional causes of diseases and improve the diagnosis of hereditary diseases. In addition to the direct examination of persons affected, the analysis of healthy family members, for example of parents, plays an important role in a so-called trio analysis, especially in the efficient filtering of the extensive data sets for newly created changes, so-called de novo- Variants (new mutations). In the context of the outlined analyzes, new disease genes can be found and validated. The gain of scientific knowledge due to a better understanding of basic cell biological mechanisms can contribute to the development of targeted therapeutic approaches. In this context, the Solve-RD project has been built and financed by the European Union with the ambitions to solve large numbers of rare disease, for which a molecular cause is not known yet by sophisticated combined omics approaches, and to improve diagnostics of rare disease patients. Solve-RD fully integrates with the newly formed European Reference Networks (ERNs) for rare diseases, and in particular the ERN-RND, -EURO-NMD, -ITHACA, and -GENTURIS. The AnDDI-Rares network is fully affiliated to the ERN ITHACA network and will actively contribute to the project, by the ambition of sharing knowledge about genes, genomic variants and phenotypes. The project will first reanalyse 18.000 negative exomes from the different ERNs performed in a diagnostic or research context (collection of biomaterial, clinical/phenotypic data plus next-generation sequencing has already been performed, and the patient/family has agreed previously in writing that their sample could be used for research related to their disease, with no study related presence required. The project will also propose new multi-omics analyses with new samples needed in 500 patients and their parents in total, justifying the AnDDI-Solve-RD project.

For the retrospective data analysis, patients with genetic diseases of any age and, if available, other family members, for whom genetic analyzes were carried out between 10/2016 and 12/2020, should be included. This equates to approximately 13,000 records, minus combined analyzes in the same patient, an estimated 12,000 individuals.

The Gene Discovery Core at The Manton Center for Orphan Disease Research based at Boston Children's Hospital studies families with rare, poorly understood or undiagnosed, but suspected genetic conditions. The primary goal of the research is to better understand the genes and proteins (gene products) involved in rare diseases. The researchers hope that our studies will allow for improved diagnosis and treatment of individuals with rare disease in the future. Individuals with any rare/undiagnosed condition are eligible to enroll. Enrollment includes: Providing DNA and tissue samples (when available) Access to participants' medical records Access to genomic data (when available) Samples are used for genetic analysis (primarily exome and genome sequencing or reanalysis) to identify the genetic cause for the individual's illness. Individual research results are returned to families through their health care provider after confirmation in a clinical lab. If a cause is identified, that can be reported back to the family through their health care provider and the study's genetic counselor. When possible, the investigators also collect samples from parents and full-siblings as well as any other affected family members.

The goal of this observational study is to identify key factors leading to psychotherapy or psychological support in adult subjects with Marfan syndrome (MSF). the main questions it aims to answer are: Understand and define which internal variables of the individual drive this request for psychological support; To learn about verify the impact that the clinical manifestations of MSF have on psychosocial aspects, self-esteem, subjective perception of the disease and coping mechanisms.

The goal of this observational study is to learn about the impact of Marfan syndrome (MFS) in paediatric affected subjects. the main questions it aims to answer are: The assessment of quality of life in MFS Italian patients; The impact of phenotypic manifestations on self-image and self-management skills; Stratify patients according to the need of psychological support. Participants will take part in the study by completing four self-report questionnaires.

The SRDR is a national registry that records rare diseases in people of any age who live in Switzerland. It serves as a platform for scientists, health professionals, affected people, and politicians.The SRDR aims to collect epidemiological data on rare diseases, and data on changes to the diagnosis over time. The SRDR will further serve as a research platform and facilitate patient participation in national and international studies. The SRDR will promote harmonization of data and method between the numerous existing disease-specific registries in Switzerland, will strengthen the exchange with international rare disease registries for research and policy, and will build a network for communication for patients and health care providers.

Despite rapidly advancing developments in targeted therapeutics and genetic sequencing, persistent limits in the accuracy and throughput of clinical phenotyping has led to a widening gap between the potential and the actual benefits realized by precision medicine. Recent advances in machine learning and image processing techniques have shown that machine learning models can identify features unrecognized by human experts and more precisely/accurately assess common measurements made in clinical practice. The investigators have developed an algorithm, termed EchoNet-LVH, to identify cardiac hypertrophy and identify patients who would benefit from additional screening for cardiac amyloidosis and will prospectively evaluate its accuracy in identifying patients whom would benefit from additional screening for cardiac amyloidosis.

During the last decades hematologists have excelled at improving and refining the classification, diagnosis, and thus ultimately the therapeutic decision-making process for their patients. This continuous evolution proceeded in parallel to seminal discoveries in basic science such as FISH, PCR and NGS. So far, the current WHO classification serves as reference to diagnostic decision making and is largely based on 5 diagnostic pillars: cytomorphology of peripheral blood and/or bone marrow smears, histology and immunohistochemistry of bone marrow trephine biopsies or lymph nodes, immunophenotyping, chromosome banding analysis supplemented by FISH analysis, molecular genetics including PCR and targeted panel sequencing via NGS. This leads to a swift diagnosis in 90 % of all cases. The leftover 10 % remain a challenge for hematopathologists and clinicians alike and are resolved through interdisciplinary teams in the context of specialized boards. With the advent of high throughput sequencing (mainly WGS and WTS) the possibility of a comprehensive and detailed portrait of the genetic alterations - specifically in challenging cases - has become a realistic alternative to classical methods. In SIRIUS the investigators will prospectively challenge this hypothesis to address the question of how often a better or final diagnosis can be delivered by WGS and/or WTS and if unclear cases can be efficiently resolved.

This prospective mixed-method interview study aims to qualitatively describe the beliefs, attitudes, and informational needs around gene therapy for rare pediatric diseases among patients and parents of children with a rare disease targeted for treatment using gene therapy techniques. Using learned insights, the team will develop an online platform providing educational content and patient decision aids for patients and their families.