'A variant of uncertain significance' and the proliferation of human disease gene databases

Current and future diagnosis of cystic fibrosis: Performance and limitations

Cystic fibrosis (CF) is the most frequent genetic disorder in the Caucasian population benefiting from systematic newborn screening tests. It is also the most frequent indication of prenatal and preimplantation genetic diagnosis for a single gene disorder. During the past thirty years, thanks in part to the evolution of diagnostic techniques, our knowledge on CFTR genetics and pathophysiological mechanisms involved in CF have significantly improved. With the implementation of newborn screening in France and in several countries, the diagnosis now often occurs in clinically asymptomatic infants and this has modified the criteria for CF diagnosis. Recently, guidelines for CF diagnosis have been reformulated in Europe and the US, in regard to sweat chloride usual values and disease terminology. This review describes the methods and molecular approaches that are used in routine practice or are being developed to detect CFTR protein dysfunction and to identify disease-causing CFTR variants. Ultimately, an optimal use of all these functional and genetic resources may improve patient care and therapeutic decision-making. © 2020 French Society of Pediatrics. Published by Elsevier Masson SAS. All rights reserved.

Locus-specific mutation databases: pitfalls and good practice based on the p53 experience

Between 50,000 and 60,000 mutations have been described in various genes that are associated with a wide variety of diseases. Reporting, storing and analysing these data is an important challenge as such data provide invaluable information for both clinical medicine and basic science. Locus-specific databases have been developed to exploit this huge volume of data. The p53 mutation database is a paradigm, as it constitutes the largest collection of somatic mutations (22,000). However, there are several biases in this database that can lead to serious erroneous interpretations. We describe several rules for mutation database management that could benefit the entire scientific community.