Clinical Research Directory

Data Collection of Patients With Rare Bone Diseases

RD-DATA is a retrospective and prospective data collection, finalized for care and research purposes. It is articulated in main sections - strongly related and mutually dependent on each other - corresponding to different data domains: personal information, clinical data, genetic data, genealogical data, surgeries, etc. This approach has been developed to corroborate and integrate data from different sources and evaluating several aspects of the diseases and to correlate genetic background and phenotypic outcomes, in order to better investigate diseases pathophysiology. Due to legal requirements, institutional directives and organizational issues, we are unable to include individuals residing outside Italy in the registry at this time. We are currently engaged in the preparation of a recruitment process for individuals residing outside Italy.

Extreme Morphology and Metabolic Health

Researchers at the University of Bath are investigating the metabolism of individuals with extreme body size, including those with skeletal dysplasia (commonly known as dwarfism), to manage health risks such as heart disease. By better understanding how body size could change how the body processes food, or how being bigger or smaller may influence eating habits, healthy living guidelines to tackle issues such as obesity and overweight in these populations can be improved. With help from expertise in the psychology field, this research will also investigate whether the mental health of these individuals has been affected by their size. On the whole, this study will involve one 24-hour visit to a research laboratory at the University of Bath, followed by a 2-week monitoring period to capture 'normal' physical activity and eating routines.

Decoding the Genetic Landscape of Skeletal Diseases

This 5-year project aims to (1) search for genetic causes for yet unsolved congenital skeletal disorders (GSDs); (2) study consequences of the newly identified pathogenic variants in cells and in transgenic mice, (3) summarize data on natural course and complications for different GSD groups. For patients with unsolved GSD, the investigators search for molecular causes of GSDs using whole genome sequencing (WGS) and total ribonucleic acid (RNA) sequencing. Candidate gene variants are selected using genome or transcriptome sequencing data, clinical findings and screening of omics databases. Causality of the new variants is studied in cells and in transgenic mice models. Molecular and clinical findings are summarized for different GSD groups.