ClinPrior: an algorithm for diagnosis and novel gene discovery by network-based prioritization

BackgroundWhole-exome sequencing (WES) and whole-genome sequencing (WGS) have become indispensable tools to solve rare Mendelian genetic conditions. Nevertheless, there is still an urgent need for sensitive, fast algorithms to maximise WES/WGS diagnostic yield in rare disease patients. Most tools devoted to this aim take advantage of patient phenotype information for prioritization of genomic data, although are often limited by incomplete gene-phenotype knowledge stored in biomedical databases and a lack of proper benchmarking on real-world patient cohorts.MethodsWe developed ClinPrior, a novel method for the analysis of WES/WGS data that ranks candidate causal variants based on the patient's standardized phenotypic features (in Human Phenotype Ontology (HPO) terms). The algorithm propagates the data through an interactome network-based prioritization approach. This algorithm was thoroughly benchmarked using a synthetic patient cohort and was subsequently tested on a heterogeneous prospective, real-world series of 135 families affected by hereditary spastic paraplegia (HSP) and/or cerebellar ataxia (CA).ResultsClinPrior successfully identified causative variants achieving a final positive diagnostic yield of 70% in our real-world cohort. This includes 10 novel candidate genes not previously associated with disease, 7 of which were functionally validated within this project. We used the knowledge generated by ClinPrior to create a specific interactome for HSP/CA disorders thus enabling future diagnoses as well as the discovery of novel disease genes.ConclusionsClinPrior is an algorithm that uses standardized phenotype information and interactome data to improve clinical genomic diagnosis. It helps in identifying atypical cases and efficiently predicts novel disease-causing genes. This leads to increasing diagnostic yield, shortening of the diagnostic Odysseys and advancing our understanding of human illnesses

Usefulness of IDEAL T2 imaging for homogenous fat suppression and reducing susceptibility. (B-0496)

none6Bignotti, B; Airaldi, S; Zaottini, F; Tagliafico, G; Martinoli, C; Tagliafico, A.Bignotti, Bianca; Airaldi, Sonia; Zaottini, Federico; Tagliafico, Giulio; Martinoli, Carlo; Tagliafico, Albert

Ultrasound for early detection of joint disease in patients with hemophilic arthropathy

Joint bleeding represents the most commonly reported type of hemorrhage in patients affected by hemophilia. Although the widespread use of prophylaxis has been able to significantly reduce the onset of arthropathy, it has been shown that a non-negligible percentage of patients develop degenerative changes in their joints despite this type of treatment. Thus, periodic monitoring of the joint status in hemophilia patients has been recommended to identify early arthropathic changes and prevent the development or progression of hemophilic arthropathy. Ultrasound (US) has proven able to detect and quantify the most relevant biomarkers of disease activity (i.e., joint effusion and synovial hypertrophy) and degenerative damages (i.e., osteo-chondral changes) by means of scoring scales of increasing disease severity. In the present review, we have detailed major literature evidence about the use of US to assess joint status in hemophilia patients, focusing on signs of disease activity and degenerative damages. In particular, we have discussed recent evidence about “point-of-care” use patients with hemophilia