Friday, September 29, 2023

A new clinical algorithm increases the rate of diagnosis of rare diseases

A research team led by Aurora Pujol, principal investigator of the CIBER area of ​​​​Rare Diseases (CIBERER) and the Bellvitge Biomedical Research Institute (IDIBELL), developed an innovative computational algorithm called ‘Clin Before‘. This algorithm shows its ability to improving the diagnosis rate of patients with rare diseases of genetic origin.

The diagnosis of rare diseases is a constant challenge in the medical field, and although whole exome sequencing (WES) and whole genome sequencing (WGS) are very valuable methods, it remains necessary to identify faster methods. Most existing tools use patient phenotypic information to prioritize genomic data, but are often limited by incomplete knowledge of gene phenotypes stored in biomedical databases and lack of evaluation in real-world patient cohorts.

The ClinPrior algorithm addresses these limitations in an innovative way. Uses standardized phenotypic patient characteristics based on the Human Phenotype Ontology, to classify candidate causal variants. Then, through a prioritization method based on a network of protein interactions, it spreads the data to identify the variants with the greatest chance of success.

In a prospective series of 135 families affected by Hereditary Spastic Paraplegia (HSP) and/or Cerebellar Ataxia (CA), two rare diseases of neurodegenerative origin, “ClinPrior has achieved a 70% positive diagnosis rate which represents double the cases diagnosed with new tools used in diagnostic centers. according to Dr. Pujol.

In addition to its direct impact on diagnosis, ClinPrior allows researchers to create a HSP/CA disorder-specific interaction network, which will enable future diagnosis and the discovery of new genes associated with these pathologies. The group led by Aurora Pujol has known for years 10 new genes that cause ultra-rare nervous system disorders.

In the words of Dr. Pujol, “ClinPrior represents a significant advance in clinical genomic diagnostics. Its focus on standardized phenotypic information and protein interaction data not only improves the identification of atypical cases, but also effectively predicts the new genes that cause disease whose relationship to human disease is unknown. “This tool allows us to reduce the tedious diagnostic process, this diagnostic Odysseys that families suffer in search of a name for of their disease for several years, and at the same time, to increase scientific knowledge about the workings of the human brain.”

In addition to the group of Dr. Pujol, CIBER research groups participated in the research. Eduardo López-Laso from the Foundation for Biomedical Research of Córdoba – FIBICO; Mireia Del Toro and Alfons Macaya from the Vall d’Hebron Research Institute – VHIR; Luis G. Gutiérrez-Solana from the Madrid Health Service; Carme Fons from Sant Joan de Deu Hospital in Barcelona and Luis A. Pérez Jurado, from Pompeu Fabra University. Also, it has collaboration with the research group of Adolfo López de Munain scientific director of CIBERNED and head of the Neurosciences Area of ​​IIS Biodonostia.

Nation World News Desk
Nation World News Desk
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