New algorithm improves rare disease diagnosis rates

Las rare diseases, also known as orphan diseases, are medical disorders that affect a very small number of people compared to the general population. In many parts of the world, a rare disease is defined as one that affects fewer than 1 in 2,000 people. These diseases can be genetic, congenital or acquired, and are often chronic, debilitating and life-threatening. Due to their low prevalence, rare diseases often present unique challenges in your diagnosis and treatment.

Now, a research team led by Aurora Pujolprincipal investigator of the CIBER area of ​​Rare Diseases (CIBERER) and the Bellvitge Biomedical Research Institute (IDIBELL), has developed an innovative computational algorithm called ‘ClinPrior‘. This algorithm has proven its ability to .

The detection 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 techniques, there remains a need to identify faster methods. Most current 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. It uses standardized phenotypic characteristics of the patient, based on the Ontology of the Human Phenotype, to classify candidate causal variants. Subsequently, through a prioritization approach based on a network of protein interactions, it propagates 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) or Cerebellar Ataxia (CA), two rare diseases of neurodegenerative origin, “ClinPrior achieved a positive diagnosis rate of 70%, which represents double the cases diagnosed with the current tools used in diagnostic centers.” according to Dr. Pujol.

In 135 families affected by Hereditary Spastic Paraplegia (HSP) or Cerebellar Ataxia (CA), “ClinPrior achieved a positive diagnosis rate of 70%, which is double the usual rate.”

In addition to its direct impact on diagnosis, ClinPrior has allowed researchers to create a network of interactions specific to HSP/CA disorders, enabling future diagnoses and the discovery of new genes associated with these pathologies. The group led by Aurora Pujol has identified in recent years 10 new genes causing ultra-rare diseases of the nervous system.

In the words of Dr. Pujol, “ClinPrior represents a crucial advance in clinical genomic diagnosis. Its focus on standardized phenotypic information and protein interaction data not only improves the identification of atypical cases, but also effectively predicts new causative genes. of diseases whose relationship with human illness did not previously exist. This tool allows us to reduce the tedious diagnostic processes, these diagnostic Odysseys that families suffer in search of a name for their illness for several years, and at the same time, increase scientific knowledge about the functioning of the human brain.”

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



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