Glutamatergic neurotransmission is crucial for brain development, wiring neuronal function, and synaptic plasticity mechanisms. Recent genetic studies showed the existence of autosomal dominant de novo GRIN gene variants associated with GRINrelated disorders (GRDs), a rare pediatric neurological disorder caused by N-methyl-D-aspartate receptor (NMDAR) dysfunction. Notwithstanding, GRIN variants identification is exponentially growing and their clinical, genetic, and functional annotations remain highly fragmented, representing a bottleneck in GRD patient's stratification. To shorten the gap between GRIN variant identification and patient stratification, we present the GRIN database (GRINdb), a publicly available, nonredundant, updated, and curated database gathering all available genetic, functional, and clinical data from more than 4000 GRIN variants. The manually curated GRINdb outputs on a web server, allowing query and retrieval of reported GRIN variants, and thus representing a fast and reliable bioinformatics resource for molecular clinical advice. Furthermore, the comprehensive mapping of GRIN variants' genetic and clinical information along NMDAR structure revealed important differences in GRIN variants' pathogenicity and clinical phenotypes, shedding light on GRIN-specific fingerprints. Overall, the GRINdb and web server is a resource for molecular stratification of GRIN variants, delivering clinical and investigational insights into GRDs.
Background
Following the broad application of new analytical methods, more and more pathophysiological processes in previously unknown diseases have been elucidated. The spectrum of clinical presentation of rare inherited metabolic diseases (IMDs) is broad and ranges from single organ involvement to multisystemic diseases. With the aim of overcoming the limited knowledge about the natural course, current diagnostic and therapeutic approaches, the project has established the first unified patient registry for IMDs that fully meets the requirements of the European Infrastructure for Rare Diseases (ERDRI).
Results
In collaboration with the European Reference Network for Rare Hereditary Metabolic Disorders (MetabERN), the Unified European registry for Inherited Metabolic Diseases (U-IMD) was established to collect patient data as an observational, non-interventional natural history study. Following the recommendations of the ERDRI the U-IMD registry uses common data elements to define the IMDs, report the clinical phenotype, describe the biochemical markers and to capture the drug treatment. Until today, more than 1100 IMD patients have been registered.
Conclusion
The U-IMD registry is the first observational, non-interventional patient registry that encompasses all known IMDs. Full semantic interoperability for other registries has been achieved, as demonstrated by the use of a minimum common core data set for equivalent description of metabolic patients in U-IMD and in the patient registry of the European Rare Kidney Disease Reference Network (ERKNet). In conclusion, the U-IMD registry will contribute to a better understanding of the long-term course of IMDs and improved patients care by understanding the natural disease course and by enabling an optimization of diagnostic and therapeutic strategies.
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