Making sense of the genome remains a work in progress
Menée aux Etats-Unis à partir de données portant sur 1,45 million de personnes ayant subi entre 2006 et 2016 un test génétique recherchant des mutations héréditaires prédisposant à certains cancers (âge médian : 49 ans, 96,6 % de femmes), cette étude analyse la proportion de variants dont la signification, jugée initialement incertaine, a été revue (probablement béinin, bénin, probablement pathogène, pathogène)
DNA sequence information has become increasingly easier and less expensive to obtain, but interpretation remains a challenge. The vast amount of variation present in the human genome reveals the scope of the problem. For instance, analysis of all protein-coding regions of the genome (an exome analysis) in 50 726 individuals found a median of more than 20 000 gene variants per person, most of them rare and hundreds not previously identified.1 Because most genomic variation has little or no observable effect on human health, laboratories must undertake careful evaluation to determine the pathogenicity of variants identified by genomic testing. Standards promulgated in 2015 call for the consideration of several different types of evidence, including clinical observation, family segregation, population prevalence, and computational and functional data.2 However, the evidence for most variants is limited, so results regarding pathogenicity are often uncertain. One common outcome is a gene variant of unknown clinical significance. Other variants are classified as likely pathogenic or benign (defined as ≥90% likelihood), yielding a 5-point classification scheme: pathogenic; likely pathogenic; variant of unknown significance; likely benign; and benign.2 Over time, a gene variant may be reclassified, changing, for example, from variants of unknown significance to likely pathogenic or vice versa. But how often does this happen and under what time frame? The report by Mersch et al3 in this issue of JAMA offers some answers to these critical questions.
JAMA , éditorial, 2017