Quantification of Phenotype Information Aids the Identification of Novel Disease Genes

Abstract

Next-generation sequencing led to the identification of many potential novel disease genes. The presence of mutations in the same gene in multiple unrelated patients is, however, a priori insufficient to establish that these genes are truly involved in the respective disease. Here, we show how phenotype information can be incorporated within statistical approaches to provide additional evidence for the causality of mutations. We developed a broadly applicable statistical model that integrates gene-specific mutation rates, cohort size, mutation type, and phenotype frequency information to assess the chance of identifying de novo mutations affecting the same gene in multiple patients with shared phenotype features. We demonstrate our approach based on the frequency of phenotype features present in a unique cohort of 6,149 patients with intellectual disability. We show that our combined approach can decrease the number of patients required to identify novel disease genes, especially for patients with combinations of rare phenotypes. In conclusion, we show how integrating genotype-phenotype information can aid significantly in the interpretation of de novo mutations in potential novel disease genes.

De novo variants in FBXO11 cause a syndromic form of intellectual disability with behavioral problems and dysmorphisms

“…It has, for example, been shown that the identification of recurrently mutated genes in individuals with an overlapping phenotype add to the interpretation of variants. This depends, however, on the rarity and specificity of the clinical feature(s) involved [10]. For instance, a combination of rare congenital abnormalities or dysmorphic features is more specific than non-syndromic ID and hypotonia on its own [10].…”

“…This depends, however, on the rarity and specificity of the clinical feature(s) involved [10]. For instance, a combination of rare congenital abnormalities or dysmorphic features is more specific than non-syndromic ID and hypotonia on its own [10]. Also, the inheritance pattern can be dependent on the severity of the ID and this may help interpretation.…”

TTC5 syndrome: Clinical and molecular spectrum of a severe and recognizable condition

“…However, hypothesizing a syndrome starting from recognized descriptive clinical criteria allows the clinician to suspect a genetic diagnosis and guide geneticists to choose the technique with the higher diagnostic yield, which is more effective economically and time-saving. Lastly, reverse phenotyping can support molecular findings, confirming the initial hypothesis and establishing the causality of novel or uncertain results (Vulto-van Silfhout et al, 2017). The tetratricopeptide repeat domain-containing protein 5 gene (TTC5) encodes a stress-inducible transcription cofactor that interacts with lysine acetyltransferase p300 and several components of the p300 complex in the nucleus (Demonacos et al, 2001).…”