Sequencing of uncertain significance

    loading  Checking for direct PDF access through Ovid

Excerpt

In the initial reports that identified the long‐QT syndrome (LQTS)‐associated genes, mutation status was proven by a combination of linkage mapping, DNA sequencing, ion channel expression analysis, and functional assessment.1 Examination of both expression and function proved providential because various mutations affected ion channel expression levels, membrane trafficking, and/or function.4 Specificity of disease association was confirmed by demonstrating absence of the identified mutations in the genotypes of a few hundred unaffected individuals. The comprehensive nature of this analysis soon proved impractical as the number of observed variants in LQTS genes increased. Functional investigations continued,5 but not at the same rate as “disease‐associated” variant reporting.7 The typical method for assigning disease association status shifted from a more comprehensive analysis to a more limited assessment that generally focused on analyzing frequency of the questionable genetic variant in databases of gene sequenced, phenotypically normal individuals. It was believed that the rarity of LQTS made it unlikely that true positives would appear with any significant frequency in a collection of normals, so variants seen in these databases were deemed less likely to be disease‐causing. The rationale for this approach rested in a study of nearly 50,000 infants in Italy using a combination of QTc measurement and genotyping that estimated the prevalence of LQTS to be approximately 1 in 2,000.9 As technology improved, the number of “normal” sequences available for comparison increased to a current standard that routinely uses databases of a few thousand people.
In this issue of Journal of Cardiovascular Electrophysiology, Kaltman et al.10 report that the current standard is inadequate. Kaltman used the gnomAD database containing 123,136 genotyped patients, and they looked for 1,415 LQTS disease‐associated variants. They found 347 of these variants in the database, of which 7 were present at an allele frequency greater than 1:1,000 and 65 were present at an allele frequency greater than 1:10,000. (Considering the reported disease prevalence, any single pathogenic variant should be found at a frequency far less than the overall LQTS population frequency of 1:2,000.) Kaltman looked more closely at the 65 identified variants and found that most lacked high quality data supporting a conclusion of pathogenicity. Only 9 of the 65 variants had published functional data, and only 5 had documented linkage with disease phenotype in family studies. Kaltman rightly pointed out that more data are required for assigning disease association status given the implications of this decision.
Of interest in Kaltman's report is the occurrence in the gnomAD database of several variants that had functional data supporting the LQTS behavior. Kaltman's findings resemble those of Norton et al., who did a similar analysis for dilated cardiomyopathy.11 Norton used the NHLBI exome sequencing project as their database of phenotypic normals. Like Kaltman, Norton found that a large percentage of reportedly causative variants in dilated cardiomyopathy were present in the normal population database. Where Kaltman and Norton differ slightly is their interpretations of this finding. Kaltman starts off their discussion by stating that “a significant number of [LQTS] variants … designated as disease‐causing or likely disease‐causing are probably mislabeled” (although to be fair, they soften this by later stating that their data “suggest that many of the variants associated with LQTS … are either bystanders, modifiers of disease, or associated with reduced penetrant forms of disease”). Norton considered but rejected the idea that the variants found in the general database were false‐positives. Instead, they postulated that these variants were low penetrance or disease susceptibility altering. Norton backs up this assertion with a discussion of the functional alterations proven for 13 of the 31 variants found in the general database.
    loading  Loading Related Articles