Cohort of diagnosed patients and gene prioritization
In this experimental model, Tomar and colleagues included 50 cases with neuromuscular disorders; all had available sequencing data, fully described phenotypes, and known causal genes. The authors varied the level of available clinical information in the HPO terms used for simulated variant analysis. Using 3 web-based gene prioritization tools on the 50 cases, they varied the HPO input to include a random selection of 10%, 30%, and 50% of HPO terms derived from deep phenotyping.
The 3 prioritization tools ranked input genes based on gene-phenotype associations that were derived from gene-phenotype databases. The authors then assessed the quality of the candidate gene lists by the location of the known causative gene on the generated rank lists. They repeated this analysis 4 times with different randomly selected HPO terms.
Inclusion of more HPO terms allowed for more accurate diagnoses in rare disorders
The authors found that the phenotype input for ES matters. When only 10% and 30% of the HPO terms were used to create a candidate gene list, the causative gene was less likely to be in the top portions of gene lists than when 50% or 100% of the available HPO terms were used.
For well-characterized disorders, use of the top 10% HPO terms performed as well as when all available HPO terms were used. For previously undescribed disease-gene associations, identification of the disease gene suffered with more limited HPO term availability.
What this study contributes
This study was a simulation of previously sequenced patients with neuromuscular disorders. It examined a small sample size for a narrow spectrum of disease. However, it clearly illustrated the principle that completeness of phenotypic information for ES pipelines is relevant for interpretation.
WHAT THIS EVIDENCE MEANS FOR PRACTICE
The quantity and quality of phenotype input into ES matters for assessing genetic variants. HPO terms have been developed to represent prenatal sonographic findings, and these have been extended to include gestational age of onset in some cases. Providing as much data as possible about the prenatal phenotype through accepted uniform vocabulary (such as HPO) will increase the likelihood that a prenatal diagnosis can be made.
The quantity and quality of phenotype input into ES matters for assessing genetic variants. HPO terms have been developed to represent prenatal sonographic findings, and these have been extended to include gestational age of onset in some cases. Providing as much data as possible about the prenatal phenotype through accepted uniform vocabulary (such as HPO) will increase the likelihood that a prenatal diagnosis can be made.
Detailed description of prenatal findings is essential to diagnosis
Aarabi M, Sniezek O, Jiang H, et al. Importance of complete phenotyping in prenatal whole exome sequencing. Hum Genet. 2018;137:175-181.
In a retrospective cohort study, Aarabi and colleagues evaluated the diagnostic utility and limitations of ES in prenatal cases with structural birth defects.4
A case series study
The investigators included 20 pregnancies with structural birth defects that were referred to their center for prenatal diagnosis between 12 and 20 weeks’ gestation. All pregnancies had normal karyotype and microarray analyses prior to enrollment.
ES was performed on trio samples, which included fetal and parental DNA samples (extracted from peripheral blood). Reports provided by the commercial laboratories were normal for all cases and included no pathogenic or likely pathogenic variants. The laboratory provided the investigators with the FASTQ (genetic sequence) files for reanalysis, which was performed using both prenatal and postnatal detailed phenotypic information.
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